Listen on Spotify, Apple, and Amazon | Watch on YouTube

Thinking about going from Big Tech to startup?

In this episode of Founded & Funded, Madrona Managing Director Tim Porter sits down with Bhrighu Sareen, who took the leap from Microsoft to Highspot and has been leading AI-driven product innovation ever since. They talk about the realities of transitioning from a massive company to a high-growth startup, scaling AI-driven teams, and how Bhrighu’s helping transform sales enablement through automation and intelligence.

His insights on navigating change, working with founders, and executing at speed are a must-listen for any leader considering the leap from stability to startup chaos.

Tune in now for practical strategies and an inside look at how AI is reshaping go-to-market execution.

---

This transcript was automatically generated and edited for clarity.

Bhrighu Sareen: Hi, Tim. Good to be here and thanks for having me. It’s always a pleasure to talk to you. I’ll say if you’re thinking about making a switch, Tim’s a really good person to speak to. I remember the first time we met, I had spoken to Robert and the co-founders a few times, and on the fence, not sure, and then Tim met me at this coffee shop in Kirkland, Washington.

Tim Porter: Zoka.

Bhrighu Sareen: Exactly, yeah. He was only, I think, 20 minutes late, maybe more and gave me some excuse about it. He was trying to raise a lot of money for the next fund or something. Not that I could verify, but we’ll believe him. So, memorable, not just from that, but thank you for always being there in terms of providing guidance and how to think about it and also specific examples from your past.

Tim Porter: Thanks, Bhrighu. That is a true story. My only defense, I don’t remember why I was late, but at least I came to you. I drove across the lake and to a coffee shop in your neighborhood.

All right, Bhrighu, why don’t we start with your journey from Microsoft to Highspot? What were you doing at Microsoft? Say a little bit more about building Teams and what inspired you to make the switch from Big Tech to startups. This is definitely a very common thing. People who have had successful careers at Big Tech companies and “Hey, I want to do something earlier stage. How do I do it? Why do I do it?” You’ve done it super successfully. Tell us about that journey.

Bhrighu Sareen: Microsoft Teams was the last project I worked on, but prior to that, I had worked in Bing, MSN, and Windows. Microsoft is a phenomenal place because you can have multiple careers without leaving the company. I got an opportunity to learn a lot, started my career there and just worked up through the levels. Numerous challenges, great managers, great mentors, and a lot of very, very smart people that allowed me to grow and challenge myself.

Teams was a phenomenal experience. It was this small product. I joined before we even went to beta, and no one knew where it would land up, but the concept of redefining how information workers actually work, reduce friction, and having to use multiple tools to get the job done was appealing. It was a phenomenal challenge, and it gave me a chance to learn. When I joined, like I mentioned, we hadn’t even shipped the product or it wasn’t even in beta, but then went from there and took it from zero monthly active users to 300 million monthly active users when I left, so phenomenal growth.

I’d been there six and a half, seven-ish years and done a lot of different roles, taken on different aspects of the product, built in PM/ENG together, ecosystem, partnerships, customer growth, and I was looking for my next challenge. I think every product person has this thing in the back of their mind like you mentioned, which is like, “Huh, should I do a startup? Is the grass greener on the other side?” I had been in Big Tech for 17-ish years with Microsoft, and so I think in priority order for me it was that I wanted a challenge, and a place where I could learn. The two different aspects, could I have taken another job at Microsoft and learned? Absolutely. I would’ve taken on a new challenge, a new dimension to it, but the depth of learning that this change allowed me to take was drastic. I think the greater the challenge, the greater the learning.

The other end of the spectrum was going from a big company to a smaller company. I report directly to the CEO, and that provides a peer group like the CFO, CHRO, so learning in terms of what are the issues that are impacting the entire company. You’re not just focused on your product area and on your scope, and that’s the only thing I’m going to do, learning in terms of speed and agility. As a startup, you don’t have a billion dollars in cash sitting in the bank. You don’t have 25,000 developers that you could pivot into whatever area you want to go. It’s just speed and agility.

Tim Porter: Teams, zero to 300 million, it’s insane to think about that kind of growth.

Bhrighu Sareen: It is. It is.

Tim Porter: I remember our first conversation, and I was struck by a few things about you. One — that this point about agility is that you seemed very much about making decisions and cutting through broader group dynamics.

Bhrighu Sareen: Exactly.

Tim Porter: Sometimes part of the art of being a good executive at a big company is how you embrace big group dynamics, and you were more sort of cut through it and had lived through this hyper-growth, so that seemed like a great fit.

Even across our portfolio there were more than one company that were recruiting you. Why did you pick Highspot? I mentioned a little bit about the product and what Highspot did. You wanted the right scenario with founders and challenge, but you had ultimately different product areas to pick. Why build in this area?

Bhrighu Sareen: Another area of learning, in addition, was I mentioned all the teams I had worked in at Microsoft, and I’d never worked in Dynamics or in anything to do with sales or MarkTech (marketing technology.) It was another dimension where I could grow in terms of a new technology, a new space, and one that was evolving very rapidly. Then, coming back specifically to Highspot, I think there are a few dimensions why. One was the people. When you’re making such a drastic change, if it doesn’t feel right in terms of the people front, it could become very, very messy.

You hear these stories about people working, and oh, man, it didn’t work out. In three to five months, they’re looking for their next opportunity, so the people was one very important part. Highspot is super lucky. The three founders, Robert, Oliver, David, are good human beings to begin with, and they care.

Second, was the space was new, and then third was Highspot, when I joined, was known for content and guidance, and that was the key thing. How do you equip salespeople with the right content at the right time? They had all the right ingredients. A lot of companies never make the switch from being a single-product company to a two-product company to a multi-product company. With our release in October 2024, what’s happened is Highspot has made that transition from a single-product company to a multi-product company.

When I saw these different ingredients, I remember after the first meeting with Robert … I got a cool story. Should I digress a little?

Tim Porter: Let’s hear it.

Bhrighu Sareen: I remember I wasn’t actively saying, “Hey, I want to leave Microsoft,” because I really enjoyed working there. Somebody mutually connected us, and it was a meeting from 4:00 to 5:00 P.M. It was 4:00 to 5:00 P.M. on a Thursday, and our offices are downtown Seattle by Pike Place Market. So, I drive up and go and meet Robert 4:00 to 5:00 P.M. One thing leads to another. When I got back into my car, it was 7:15 P.M. I called the person that mutually connected us, and this person’s like, “How’d it go?” I said, “I think it went well, but I think Robert was just being nice because we were supposed to be done at 5:00. We finished at 7:15.” And he’s like, “No, no, no, no. Robert’s met other people. Usually, it doesn’t go this long.”

You feel that connection, and so when I went back the next time to meet Robert, I was like, “Hey, you’ve built an LMS. You have a CMS. You’ve got all these different pieces. If we stitch this together, Highspot’s time can be significantly greater than what it is right now based on the product offering you have.” So, when you take all those three or four things combined together, it felt like it was a good place to be.

Tim Porter: Fantastic. I want to come back to how you’ve worked with these founders. When you joined Highspot, there were, and there still are, three founders who are super active in the company: Robert, Oliver, and David. We did a podcast, Oliver and I, five years ago about Highspot. That’s one of my favorites ever. You and Oliver work super closely together now on product?

Bhrighu Sareen: Yes.

Tim Porter: All three are really involved, which has been such an amazing part of this company, but also, in theory, not easy coming in and having this big role. You’re running half the company, product engineering, yet there are these three founders who are all very opinionated around product and engineering. Yet, it’s worked out. What has it been like coming in in your role and working effectively with founders?

Bhrighu Sareen: I’m super grateful to Robert, Oliver, and David. One, for giving me the opportunity and two, how they welcomed and included me into Highspot. A bunch of friends of mine gave me advice that this was going to be a really bad idea because they’re actively, actively involved. Like you said, they have opinions. They have more contacts than I can ever have because they’ve been doing this for a decade.

Tim Porter: Absolutely.

Bhrighu Sareen: They have more knowledge. They have more connections. They have more foresight, because I had never worked in this space. David was doing the show before I joined, and I’ve said this to David. I would not have been even half as successful or delivered even one-tenth the impact for Highspot if it weren’t for David. David has been this voice in my ear all the time, selflessly giving me advice, giving me guidance, whether it was people, product, process, or strategy. Hey, Bhrighu, here’s the pitfalls. Watch out for this. Watch out for that. He does it in a super humble way. He’s not being arrogant. He’s not trying to show me down. You could have said, “Okay, hey, great job. We got someone, good luck. If you have questions, let me know.” But being proactive about helping me and helping us move forward, so super grateful to David for that.

Tim Porter: I think there’s a question I framed around how you navigated it, but there’s a great message to founders here around how you onboard a new exec, empower them, get them ready, work together with them, and I think that’s super critical. I was going to ask how did you get comfortable with that, if that was going to be the case? Unfortunately, I’ve seen some cases where, “yeah, I talked it through with the founders. They said they wanted me to be there, and then it turned out they didn’t.” On some level, it’s a human thing, and you build trust. Was there anything on how you got confidence that they were serious about not just saying that we’re ready to bring somebody else in and do all the things you mentioned that David has done to help make you successful?

Bhrighu Sareen: Two things. One is — if you remind yourself that we’re all going to win together, it isn’t as if David or Oliver are going to have a different outcome than I’m going to have. So, I tell myself, “Okay, are they coming from the right place? And wherever we’re going, whatever decision we’re making, is it going to take Highspot to the next level?” If you think about Highspot first — is it the right decision? Then it becomes easy. Then it’s not about ego. Is your idea right, or is my idea right? It doesn’t matter. Is it the right idea for Highspot?

Tim Porter: Clearly, these folks wanted to win.

Bhrighu Sareen: Exactly, and so if you come in with an attitude to win, with an insane bias for action, and are humble enough to say, “okay, we learned” because not all decisions will be positive, “We learned from that, and now we’re going to go back and fix it,” I think it’s hard. Even the human nature part I think because founders in general have a different mindset, but these three things should align with every founder out there.

Tim Porter: So, having a great partner on the engineering and product side in David and Oliver.

Bhrighu Sareen: Yes.

Tim Porter: Robert is probably the best strategic product vision exec I’ve ever worked with. I remember seeing that way back at Microsoft and now, in the last 12 years at Highspot, but it can also be hard for you. He’s always the head of product in some ways, and that’s made the company so successful. How has that dynamic been?

Bhrighu Sareen: One other suggestion I’d make to the folks listening is communication is key, and building relationships is key. Yes, all three founders are Microsoft, and so was I, but our paths never crossed. I had never spoken to these folks. A lot of people say, “Oh, yeah, this was easy. You picked Highspot because they were Microsoft. You probably interacted with each other, and then they pulled you over.” I’m like, “I did not know the individuals by first name, last name or even existed.” We had never crossed paths, whether in social circles or at work. When you’re starting new, commit to frequent communication and building trust.

One of the things that we put in place was every Tuesday, Robert and I have lunch. The second thing we do is the three founders, and I would meet every Tuesday as well. Initially, they committed to actually sharing context, helping me grow. We said, “Hey, we’ll do this for three months-ish. I’ll be ramped up. Four months, you’ll have enough context, and we’ll cancel the meeting. We don’t need it.” Fast forward two-plus years, we still meet every Tuesday, all the three founders and myself.

Tim Porter: It’s often simple, smart mechanisms that are persistently applied.

Bhrighu Sareen: Yeah, there’s no shortcuts.

Tim Porter: There’s no substitute.

Bhrighu Sareen: Exactly. There’s no substitute, absolutely. There’s no shortcut in building trust. You have to put in the time. I think, animosity builds up when you are making stories up in your mind. He said this, so he actually means that, or she said that, so this is what’s going to happen. Why don’t you ask them what they mean? But you’re so busy in your day-to-day life that you don’t. So, my lunch with Robert every Tuesday forces us to discuss a whole bunch of things.

Tim Porter: Maybe mention some of the initiatives or structural things that you’ve done at Highspot. As someone on the board, I’ve been struck overall by how the company’s gotten more efficient, but also shipping even more things, the velocity of things. Your shipping is amazing. You’ve done some things around team and offshore but talk about some of the things that you put in place, building on the great foundation that the founders and others had built and how that’s gone. Has it all been easy? Has it been challenging? What’s it been like?

Bhrighu Sareen: A super complicated question. I’m not sure where to go because you’ve thrown in “puting structural things in place, how do you increase product velocity, how did you get our costs into control.”

Tim Porter: We can throw you a softball. You can take it in any direction. Specifically, how would you describe the major initiatives that you had to put in place when you got to Highspot from a product and engineering standpoint?

Bhrighu Sareen: I lived it the last two-plus years now, and when I joined, I have to start by saying everyone’s heart was in the right place. The clarity of where we were going was always there, and that’s super important because if your founders, the exec team, the VPs, senior directors, directors, and so on and so forth aren’t clear on where we’re going, that’s a big problem. At least those two parts where everyone’s heart is in the right place.

So, then coming back to the question you asked with that context is we realized that the company was growth at all costs. Before I joined, the previous 18 months or two years was phenomenal. We’ve been hiring people all over North America, and so now that you have clarity of where you want to go, how do we make sure that we maintain the velocity by removing roadblocks for the crews. We identified that our smallest unit of impact is actually a crew, and one of the things we put in place was something we called an edge meeting because your ICs are the edge.

Tim Porter: How big are crews, roughly?

Bhrighu Sareen: Eight to 10 with a product manager, an engineering manager, a bunch of IC engineers, and a designer. So, the crew is your unit of work, and they’re the ones that get stuck because it could be cross-team dependency, it could be because the designer is working on some other project, they aren’t clear on the architecture, or they’ve taken a decision that three months later you got to rework. The product leadership team decided that every two weeks we’re going to meet every single crew. Every week we do crews one, two, let’s say 12, and then 13 to 24 will be next week.

We were spending about 15 hours a week, and initially, the teams were like, “Whoa, whoa, whoa. This is micromanagement. It’s a bad idea, or it’s a waste of our time.” And I said, “One second. Except for the product leadership team who’s going to be in all the meetings, for a crew, you’re only spending one hour every two weeks.” But what it allowed the crews to do, when you look back everyone’s like, “Oh, this was great.” The uber concept around that was enable every discipline to have a voice to raise any issue in an open and transparent manner that is predictable.

It isn’t because some PM and engineer had a meeting with our VP of engineering, and they took a decision, so the design team was like, “Hey, you left us out.” It wasn’t as if they were doing this out of bad intent. It was just because the speed at which we wanted to move, if you met someone, and you got on a Zoom call, you took a decision, you moved on. It wasn’t because I’m purposely leaving the engineer out, I’m leaving the PM out. So, whoever got to the decision makers, took a decision, got a roadblock moved, and they will move forward.

That edge meeting thing was initially hard for people to say if it was worth it, but now, when you look back, engineers bring in architecture documents. PMs bring in specs. We look at Figmas, and we’ve just been able to remove so many blocks.

Tim Porter: Making sure everyone has a voice, smaller teams where everyone can be heard, and then also the frequency increased. So, instead of every other week, how often do you have this now?

Bhrighu Sareen: No, it is still every two weeks.

Tim Porter: Okay, got it. They get much more out of those times together.

Bhrighu Sareen: Correct, but if they need additional time, they can always ask for it. But it’s predictable, as in everybody in the company knows, “Oh, this particular crew is going to have a review at this particular time.”

Tim Porter: That’s fantastic.

Bhrighu Sareen: Then one more thing that I did because you asked, “Hey, what are the structural things,” one other thing I did was cross-team dependencies, usually for companies, depending on the size, whether you’re mid-size or larger, even Big Tech, one crew can never ship an entire thing. They’re dependent on some infrastructure pieces, a cross-team, or UX, or whatever it might be. One interesting thing happened six months after we put this thing in place. A particular crew comes up and says, “Hey, we are unable to ship this.” We’re like, “Why is that the case?” “Oh, because we have a dependency on this other crew, and they’re unable to do it.”

So, we evolved the edge meeting to say any crew can summon any other crew, or any crew can join any other crew because it’s transparent. Everyone knows the schedule, which crew’s presenting when, and they can come in. It did a phenomenal thing. 90% of cross-team dependencies get resolved before they ever show up to the PLT. You have a crew. I have a crew. We’re PMs. Each of the crews are like, “Hey Tim, I really need you to show up to the product leadership team, our edge meeting. We want you in there because there’s dependency.” Tim’s like, “Oh.” You’re like, “Hey, hey, can we just resolve this right here?”

Tim Porter: Absolutely. Create an environment where teams can work it out amongst themselves and not have to bring everything up and bubble it up at a much faster pace. That’s fantastic. Maybe talk a little bit about how you’ve organized around offshore and a few centers of excellence. I know a big topic of conversation for lots of companies is back to office and being together, but then there’s also a need to be able to have engineering groups in other geographies for various reasons. I think you’ve done a nice job of finding a great way to do that. Maybe describe how you’ve done that.

Bhrighu Sareen: I started in September 2022, and if there are folks listening to this that are considering this move and you’ve always been like, “I was always in product and never in other kinds of roles,” if you’re thinking of joining or once you join, I would recommend sitting down with a CFO, VP of finance to understand how the numbers work. Chris Larson, our CFO was super gracious with his time, and after I started in September ’22, showed me the numbers. ’22 was this interesting year where, in the second half of ’22, things had started slowing down, and people weren’t sure what was going to happen to the economy. Are we going to enter a recession? Is it going to be soft landing? It could go any which way.

I look at the numbers, and I’m like, “Hmm, if our goal is to hit profitability, it doesn’t feel like we’re going to, this glide path isn’t moving in the right direction.” After getting educated, I realized we’ve got to make a few changes. One of the things we looked at was, we want access to a lot more talent, and can we do it, where can we do it, and how would it work out? The first thing we did was in November of ’22 with my direct reports, and through a connection at the Canadian Consulate in Seattle, we actually went up and met the government of British Columbia. From Seattle to Vancouver, it’s only a three, two and a half, three-hour, depending how fast you drive, Tim, two and a half drive or a three-hour train ride, and it’s super convenient. You could do a day trip if you needed to where you can meet the team, spend time.

We got a lot of good support from the government of BC, and we decided to open up an office in Vancouver, Canada. When we started, we said, “Hey, over a two-year period, we’ll put about 50 people in Canada in Vancouver.” Actually, in 18 months, we had already hit 50 people, and that provided us the ability to have our first distributed beyond remote. We were already doing remote before I joined Highspot, but it allowed us to have a center of excellence, access to a lot of talent, and allowed our engineers and leaders to see could we do a remote center and practice before we do something big.

Then after we saw that working, we decided to start a development center in India. Now, that was a lot of debate internally. A lot. You can imagine all the different reasons why we should not do it and maybe a couple of reasons why we should, but we moved forward. Again, this is about agility, speed, let’s try things out, and India offered Highspot access to an insane amount of talent. Over the last two and a half decades, talent in India has evolved. You could always get really good college hires. Over the last two and a half decades, so many companies have opened up offices there. What that has allowed us is middle management, and typically having the right managers will help you because they can coach, mentor, grow the early-in-career talent. That matters. Then senior leadership, there’s actually a decent population of team leadership who could run your development center in India.

Tim Porter: That’s been key for you. You have a great leader on the ground.

Bhrighu Sareen: Gurpreet.

Tim Porter: He’s been an awesome partner in making this work and growing it.

Bhrighu Sareen: That brings me to the other point I was going to make, which is the Indian population outside of India who have lived here, who have worked for these companies, a lot of them are actually moving back. Gurpreet actually spent, I think, 30-plus years in the United States, and then for family reasons, he wanted to move back. So, he moves back, and all of that knowledge on how to work with an American company, how to work cross-geo, how to work cross-time zone, how to actually have conversations with customers because when you’re building product, end-to-end ownership, there will be moments when they’re going to talk to your customers, and you want to feel comfortable that they can handle that situation.

Gurpreet is a great example of having a leader who can take an office of zero, and real stats, July of ’23 is when he signed his employment offer. Fast forward to September of ’23, we had four employees, Gurpreet, two engineers, and a designer. Fast forward right now, we have 125 people there and lots of open positions.

Tim Porter: Fantastic. We’ve been talking about things that have gone well, and coming to an earlier-stage company from a big company, I’m sure it’s not always that way. There’ve been challenges. We’ve managed through them really well. Just for the listeners, what was a surprise? You had a good sense with this team and everything, but there’s still surprises. Was there something that was a surprise that like, “Hey, this was a big transition to go from the big company, lots of resources to something smaller,” and how did you deal with that?

Bhrighu Sareen: I think if I were to prioritize all the challenges, I think the number one was how drastically the economy changed.

Tim Porter:
Yeah, there was a big externality that came about that wasn’t really expected to the extent that it hit.

Bhrighu Sareen: Exactly. I’m changing jobs, changing scale, changing employer, changing manager, changing technology, changing all these different dimensions, and then the last thing you expect is we tried coming from the middle of nowhere you’re like, “Oh, my gosh, what’s going to happen now?” But if you ask me how do you think about it, I actually look at it from another perspective, which is like I said earlier, my number one goal was learning a number of different dimensions. Guess what? That learning just got accelerated, and when you come out the other end, you’re going to be, “Huh, I did all of the things I was trying to go learn but then did it in an environment that might not show up.”

It gets cyclical, so it will show up at some point, but maybe not for another five years, four years, 10 years. Who knows what the exact timeline is? But that, I think, was the biggest challenge. You’re on our board, so those board meetings were interesting where, okay, burn. Your burn rate is crazy, but hey, can we just raise money like we have been every single round previously before. Somehow money dries up. The goals that the market is expecting you to hit change, and the company had never done layoffs before. Brutal. I think it’s just super hard.

Tim Porter: It was a hard period. The biggest thing is that a company like Highspot that had been growing meteorically in a large part as existing accounts were just hiring lots more go-to-market people, seat-based, and so the renewal rates just kept going up and up and up, and all of a sudden, all our customers budgets didn’t just get frozen, they got slashed.

Bhrighu Sareen: Correct.

Tim Porter: But we managed to keep innovating through that, find more things that give them an add-value while also getting efficient ourselves through some of the things we’ve been talking about.

Bhrighu Sareen: Exactly. So, the second thing I’d say on that topic, the previous question you asked, which was you touched on a really good point because we’ve all heard stories that x amount of companies during the dot-com bust actually decided not to do product innovation and just ride it, or through the financial crisis, not do product innovation and just ride through it and save money and conserve cash. But thanks to the folks on the board and the leadership team, we decided to just say, “No, we’re going to make this transition,” and now we’re seeing the fruits of that investment decision actually start paying off.

Tim Porter: That’s perfect. Let’s talk about that. Highspot’s always been an ML-based company. I think of the very early days, and how do you find all the sales content. Well, if you get the right signals and you put those into an ML system, you can find the right things more effectively, but it wasn’t AI in the way it is now. Talk about some of those. Give some examples. What are the things that you’re shipping? How do you use AI today? We can dig into that a little bit. Every company’s becoming an AI company, but Highspot is really there and has it in production with customers.

Bhrighu Sareen: You’re absolutely right. There’s patents with our co-founder’s names on it and other folks on there around ML technology and things of that. One of the interesting things, because also the stage we’re in right now, there’s the hype cycle where the trough of disillusionment, I think, is where we are right now. A number of our customers asked us, saying, “Hey, is any of this thing real, or is it all just hype?” What I had to land with them is if you’re Big Tech and you’re trying to reason over the significant amount of data you have for an individual, it could be across their emails and meetings and calendar and everything else, there’s three dimensions. It’s like how much compute do you want to put against it, or what’s the latency because if you give the large language models or your algorithm enough time, it will actually give you the right answer, or three is the cost. How many dollars do you want to throw at this problem, or every time there’s a query that’s sent?

I was talking to some of our customers saying in relation to that, the amount of data Highspot has to reason over for a particular individual or across an entire domain or entire customer is tiny. It’s super tiny in comparison to what the technology allows us to do today. It’s tiny. Two, there’s a number of dimensions that we could put together offline, so process it once a night, so the latency part gets taken care of, and there are real scenarios with real value.

As an example, most companies do a sales kickoff once a year. You bring your sales people together, you have a conversation, and you share the new products you’re launching. In some cases, they’ll ask them to do a golden pitch deck, which is marketing’s created the pitch deck. Let’s say we’re colleagues sitting around a table at the sales kickoff or you’re my manager. What I’ll do is I will read up, learn about it, and then I’m going to pitch it to you. You’ve got a rubric. You will score me on those things, and then I’ll do the same back for you. That’s expensive because you have to take people offline out of their day jobs, go get them to do this, or you have sales people record it, then the managers have to take time out and score.

A lot of managed sales managers are like, “I need to hit quota this month. I don’t have time for this.” So, we built a feature as part of our training and coaching product where the person creating the learning and development, the training has the training, has a rubric, verbal and nonverbal skills that they’re looking for for the salesperson to be successful, and saying the right words or how the pitch should come out. A fintech company used this and sent it around and got 800 responses back. Then the manager gets to see the video recording, the rubric. The AI uses the rubric that was provided to grade all 800 of these.

What we saw was in 55% of the cases, the manager left the AI-graded feedback as is. In another whatever 91% minus 55 is, in those cases, they either added or deleted one sentence, and only 9% of cases did managers actually delete what AI recommended as feedback and rewrite it.

Tim Porter: Wow.

Bhrighu Sareen: This financial services company, not fintech, huge financial service company, super impressed, and they’re actually now rolling it out. There’s a few hundred people, 800 or so that had access to it. Now, they’re talking about thousands of licenses for this one feature because the value and the time they’re getting back is significant.

The focus on features that will save salespeople, marketing people, support services, learning and development people that are creating it time and showing the right ROI. I can go on feature after feature after feature that’s been resonating.

Tim Porter: That’s awesome. This is this AI, real-time coaching in that the AI is really working both, and the feedback is accurate in that the manager doesn’t have to rewrite it. Then you see the impact with the end users.

There are a bunch of features. You talk about the Highspot AI Copilot. There’s the ways you do score carding. There’s ways you do content summarization, auto document generation. I think people are interested that maybe don’t know Highspot. Yes, they can go read the website, but maybe just rattle off a couple of these other new features in how you use AI for customers.

Bhrighu Sareen: Yeah, perfect. One other one that I’ll talk about is a lot of organizations have a system of record for their CRM, like for the customers. They have a system of record for, let’s say, that’s the ERP, but today, they don’t have a system of record for their go-to-market initiatives. It’s super interesting because you have so many different disciplines that have come together to actually take an initiative.

One of the initiatives as an example, and I’ll use that to just outline the capabilities we’re talking about, which is in during 2022, 2023, the CFO or the VP of finance inserted themselves in the buying process. We saw more and more sales cycles were getting elongated, and it wasn’t just procurement being able to, once the solution owner says, “I want to buy this particular product,” the procurement does the paperwork and is able to negotiate and get the deal done, but finance was like, “Whoa, whoa, whoa. We need to make sure this spend is happening. Is it correct? Is it worth it?”
There were initiatives that a lot of our customers wanted to roll out, which were: how do we train our salespeople to talk to the finance people? They do it with all our training. Now, if one of your initiatives was to increase expansion on product line ABC, there are so many pieces that have to come together for that to be successful. One is what content will get used, and is it being used? Is it created? Is it effective? How do we provide training? For example, one of the training could be financials, like how to talk to people in finance, and then product training on whatever the product line it is that you’re talking about. What’s the right sales play to use? Here’s a digital room. All these are capabilities that Highspot has, but you include it in your initiative.

Then, you want the ability to say, “Okay, all this training that I’m providing, the keywords I want to use, are they being used?” So, how do you check that? The really cool thing is today, a lot of meetings are getting recorded, and so Highspot’s conversational intelligence capabilities, again using AI and other aspects is not only able to draw out who said what, but then understand the intent behind that, so now you can have a single scorecard, a system of record for here’s all the initiatives that we care about. Here’s the cohorts because it could be a mid-market initiative, it could be an enterprise targeting enterprise customers or mid-market customers or commercial customers.

Then, in a single view, if you can have a conversation with your CRO and say, “All right, this is the content being used. Here’s how it’s being used.” Your CMO can look at how it’s performing and decide if they need to make changes. You can see the impact of all the training in real time and look at your salespeople. Are they saying the right thing? How are customers responding back to it? Again, it shows up in your initiative, and you can look at individuals, like I said in the case of the other previous example, where you can see, hey, this rep, for example, on these 12 metrics, on eight of them, you’re doing really well, nine of them you’re doing well, but on these three of them you could actually do a little better.

Highspot is that one unified platform that you go from content to guidance to understanding what’s happening with the salespeople, what skills and competencies they need to get better and then recommend the training because a lot of platforms out there today can tell you, “Hey, this meeting went well. Here’s the agenda. Here’s the topics that we discussed. Here’s aspects of the intelligence around the meeting.” That aspect is now a commodity. But when you have to take action on that, “Oh, they could have used the meetings over now. Send a digital room with this aspect. Highspot can do that. You want to take another action around, here’s a set of skills that you could do better in. Highspot can do that. Now, recommend a training based on the skills they need to improve in. Highspot can do that.

You want to now be able to follow a sales play because we’ve combined data with CRM to then say, “Okay, this is a pre-sales opportunity in the financial services business. Marketing has created this template. Let’s automatically generate a document, the presentation that will go for this particular thing, and bring in pricing if you choose to do that.”

Tim Porter: It’s so cool and illustrative that it’s such an integrative story from purely the customer’s perspective who doesn’t necessarily care about technology. They want outcomes. I see this across so many of the companies, even the very early startups, all this time and effort on we’re going to do this initiative, we’re going to do this campaign, we’re going to launch this thing, and so we have to get everybody ready. We have to train them. Then, at the end, or as it’s going, you see results like is revenue going up or down, and you can see individual reps are hitting quota or they’re not. But the why within that is so hard to tease apart.

Bhrighu Sareen: Exactly.

Tim Porter: So, you can go from all the way from the how do we train folks to what were the actions to what ultimately is working, and that way drive more revenue, more efficiency, the two golden things. Every company is like, “How do we get more revenue? How do we get it more efficiently?” So, not only is it an integrative experience for the customer, but you’re using AI in so many different ways.

Bhrighu Sareen: Exactly.

Tim Porter: Call recording and insights, automatically generating content, analyzing it, so that’s pretty neat, too.

Bhrighu Sareen: Recommending content.

Tim Porter: Recommending content.

Bhrighu Sareen: A lot of different aspects.

Tim Porter: Putting it together. What does that mean? We invest in new startups. There’s lots of innovation happening in AI, and one of the exciting things about it is you can build things really fast that have an impact. There’s a lot in your space. There’s a lot of cool things happening around the AI SDR or all the different pieces across sales even. How are you thinking about all of those startups and the opportunity for them to innovate versus what Highspot’s doing?

Bhrighu Sareen: Tim, I’m going to go back to something you said to me in ’22.

Tim Porter: Uh-oh.

Bhrighu Sareen: It was something interesting you said that there was a realization in the startup world that a lot of companies that got funding prior to ’22, it was a feature, but it could grow up to become a standalone company. I don’t remember your exact words, but my takeaway was that there was a number of startups that could have very, very good outcomes, but as opposed to being standalone, their outcome will be as a capability as part of a bigger product, something like that.

Tim Porter: Yep.

Bhrighu Sareen: That stuck with me because when I look at a startup, especially early stage, if you have a great idea, that’s awesome. Keep going, but know when it is time to be part of a bigger thing. You think it’s a really cool idea, it’s growing well, you’ve found product market fit. Either you have to start expanding into verticals or areas or product spaces that are adjacent, or you have to figure out when’s the right time to say, “Okay, I got to just be part of a bigger product.”

Tim Porter: It also, to connect back to something you referenced earlier, it often comes back to data too, doesn’t it?

Bhrighu Sareen: Oh, yeah.

Tim Porter: Access to data.

Bhrighu Sareen: Yeah, that’s another good point. Super good point, yes.

Tim Porter: You mentioned the big Co’s, like your former employer, they just have so much data across everything.

Bhrighu Sareen: Insane.

Tim Porter: Yes, it’s almost always better to have more data than less data, but it also creates challenges around, it’s just super expensive to process all of that. Then you have new companies — where it’s like, do you have enough of a data set? In your case, you said you don’t have that big of data relative to someone like Microsoft, but yet, I’m thinking through some of our biggest customers, some of the biggest technology companies, the biggest logistics companies, financial services companies, medical device companies, you have their whole corpus of sales, marketing, content docs, decks, white papers, et cetera. Is there something about having the right amount of data for these feeds? Say more about that.

Bhrighu Sareen: You’re absolutely right. People always say, “Hey, get all the data. Get all the data. Get all the data,” but you’ve got to figure out the right sweet spot for the scenario you’re trying to deliver. I think that’s something we’ve been very disciplined about internally is getting the data, cleaning the data, attaching it, and getting the right insights around the data. Then I think just as important, switching tracks as I agree with the point you made, is the user experience. I think as startups you have to decide, “I want to be the single pane of glass where everybody shows up.” But guess what? I think Teams, Slack, Zoom, Outlook, and Gmail are the horizontal applications where regardless of whether you’re a sales, marketing, finance, procurement, engineer, PM, or designer, you’re going to spend your time. That’s where you’re spending your time. Those are the tools you’re spending your time in.

Then you have role-specific. If you’re a designer, it could be Figma. It could be Adobe. If you’re a finance person, you have your own application. If you’re a salesperson, it’s CRM. So, there’s a set of horizontal applications that people spend their time in. The UX part, I think, is another aspect which a lot of companies need to make a decision is are you going to say that your data and your insights or the AI experiences that you’ve generated should only stay in your own and operated properties, or is it okay to show up inside Zoom, Slack, Teams, Outlook, Gmail where users are today?

Then there’s another question you’ve got to ask yourself is the new user experiences around these agents and co-pilots, do you surface your data, your insights there or not? Then, once you figure out the data, insights, user experience, once you figure out that stack, what do you do about the business model? Let’s say I’m a customer, and you’re here to sell me. And I said, “Hey, I’ve built my own internal copilot, like that’s our company-wide thing. I love this insight around content recommendation,” That’s a great example, “and our salesperson is sending out an email. Our co-pilot sits inside our email platform whether it’s Outlook or Gmail, and we want you to plug into that. So, we don’t really need to buy this other whole thing because we’re not using the product. We’re not using the scenario inside your product. We just want API access, so we’ll just pay for a data transfer fee, and that’s good enough.”

But you’re like, “Wait a second. I ran all the analysis, and I’m delivering you an insight. I’m not just delivering you something over an API for access to data.” These are interesting conversations that we’re going to have to have.

Tim Porter: Let’s put our future hats on here. So much continues to happen in this space with AI. Agents are a big topic of conversation. Salesforce is certainly talking about those a lot and lots of new startups. If you think a year or two ahead, maybe pick a year ahead, what are some of the things in AI you’re most excited about that Highspot will maybe be going to in that timeframe?

Bhrighu Sareen: Last year, you would’ve asked this question — you would not have used the word agent. You would’ve used the word co-pilot if we had recorded it. This year, you’re calling it agent. Two years from now, I have no idea what is going to get called, but the one thing that I am confident about is that month over month just because the speed of innovation is amazing. It’s such an amazing time to be in tech. I think every decade we say this is an amazing time to be in tech.

Tim Porter: It keeps being right.

Bhrighu Sareen: Yeah. It continues to be an amazing time to be in tech because every month, it doesn’t matter what you’re working with, whether it’s a big company or a small company or a medium-sized company or you’re thinking of starting something new, if you ask yourself, and we ask ourselves this thing is, how do we take advantage of the technology that we have access to provide value to that task in a day, to that user. So, regardless of what it’s called, if we focus on that and our list of capabilities where we can have measurable return back to our customers and delight, I think that’s the two things.

A lot of times it’s like, “Oh, the ROI is huge or not, but can you also have delight?” A lot of companies focus on ROI. Very few focus on the delight, and we have this unique opportunity where I have a 200-slide deck, which is actually a library that I have to then customize before I go present. I’m a salesperson before I present to the customer, and then they would spend, I don’t know, an hour, two hours to do that, putting in the right logo. The logo is not the right size. Making it smaller, making it bigger, all kinds of things. The delight of being able to complete that by answering four questions and getting it done in six minutes — mind blowing. The look on the reps’ faces is priceless.
So, Tim, I’m not sure what we’re going to call it, but I would say focusing on return and delighting the customers. I think that will be.

Tim Porter: What I hear you saying is there’s going to be ongoing radical productivity gains and being able to do tasks so much faster, maybe more accurately. Just so you’re not the only one putting yourself out there, I think there is a huge thing to this agent notion, and yes, it’s a newer naming, but where people will be able to interact with Highspot through natural language, through voice, and the system will complete tasks for them. So, to your point about reducing steps, et cetera, it might be the same outcomes, but getting there faster and the system does more of it autonomously, my guess is we’ll be talking about that in your user conference in the year or two to come.

Well, Bhrighu, thank you so much. Thanks for all you’re doing at Highspot. Thanks for this great advice on innovating in AI and thinking about making the jump from a big company to an earlier-stage company and super excited to see what we’re going to go build in years to come.

Bhrighu Sareen: Perfect. Thank you very much.

Tim Porter: Thanks so much for being here.

Bhrighu Sareen: Tim, thank you for having me. Thank you very much.

Listen on Spotify, Apple, and Amazon | Watch on YouTube

What does it take to go from engineer to founder, from startup CEO to scale CEO? In this special live episode of Founded & Funded, Madrona Managing Director Karan Mehandru sits down with Mohit Aron, founder of Nutanix and Cohesity, to uncover the lessons behind his success. Mohit shares his unique hiring strategy, how to identify product-market fit, and the power of balancing vision with execution. Whether you’re navigating your first company or scaling your third, Mohit’s advice is a masterclass in resilience, grit, and building a legacy.

---

This transcript was automatically generated and edited for clarity.

Karan: I have a lot of questions for you, so I’m going to pull up my notes here to make sure I don’t miss anything. If you do it once, you’re lucky. If you do it twice, I feel like there’s a lot of skill. So the first question I have for you is, did you always know that you were built to be a founder? And what do you think the best founders have as far as capabilities, characteristics, traits? What does it take to be one that scales these companies to multiple tens of billions of dollars versus ones that fizzle out? Where do you begin?

Mohit Aron: All right. I’ll say for the first part, did I always know that I am meant to be a founder? Heck, no. All I knew was that I liked to put myself into uncomfortable situations. And that’s what it takes, number one, to be a founder because if you’re just sitting in a comfortable position, you’re not going to be a founder. So, trying to be a founder was just one more attempt to put myself in an uncomfortable position. That’s how I began.

Karan: Maybe they have cryogenic chambers for that. You can run a marathon, but you ended up starting a company.

Mohit Aron: It’s the one thing that I thought, “Let me put myself into yet more ways to make myself uncomfortable.” What it means to me to be a founder is, are you passionate enough to solve a certain problem? I’ve seen people build companies for the wrong reason. A lot of people build companies for the sake of building a company, or just to be a founder. That’s the wrong reason to build a company. Another reason why people build companies is, “Oh, I want to make a lot of money.” It’s also the wrong reason. If you want to shoot for that reason, if you want to build a company for making a lot of money, you’ll probably make some but you’ll not a lot. I promise you that. Because building a great company requires a lot of ups and downs. The minute you have a down, you’re probably going to get cold feet and you’re going, “Okay, let me go do something else.” Maybe, start another company, right? And now, you’ve potentially left a lot of potential on the table.

So if you are really passionate about some problem, then, and only then, you have an opportunity to really build a great company. As part of building a company, there’s going to be lots of ups and downs. And so, what your passion for shooting behind solving that problem means that you’re going to persist. Persistence and grit is one of the key things you need to have because you’re going to fall down a lot of times, no matter how many times you’ve done it before. For me, that’s what it means to be a founder.

Karan: That’s great. One of the things that I’ve repeated multiple times is that the probability you build a $10 billion company is inversely proportional to the number of times you state that as your goal. And it’s very true in your case, having known you for almost a decade and a half now.

You made three transitions in your career that are really hard to make. You went from a non-founding engineer to a founder, then you went from a founding CTO to a startup CEO, and then you went from a startup CEO to a scale CEO. Each one of these has its own set of challenges. Walk us through what the challenges were as you made each one of these transitions. What were things you had to leave behind? What were the new traits that you had to pick up?

Mohit Aron: Sometimes people who are employees ask this question, how come the founder has such an outsized equity or whatever? I also used to ask that. The answer is that eventually, the buck stops with the founder. Everything that goes wrong, eventually, is the founder’s problem. The employees are just doing that one thing.

Karan: It may not be your fault, but it is your problem.

Mohit Aron: That is right. You get blamed for everything, and that’s the first big jump I had to make. That as a founder, whether or not it was because of me, I owned it.

Karan: It’s the owner mentality.

Mohit Aron: It’s the owner mentality. That also means that you’re doing things that you’re not expert at. That was the first big thing that I had to become comfortable with. The second thing was hiring. Again, as a non-founder, maybe you hire people that are in your areas of expertise. As a founder, you’re now hiring people that so are not in your area of expertise. You have to learn and you have to keep them happy, because guess what? If you hire great people, they also have lots of other opportunities. Even if they decide to join you right now, if you can’t keep them happy, there’s plenty of companies. Plenty of great companies that VCs found, right? It doesn’t take long for them to jump ship.

So, becoming a people person at the same time as you are doing what you do best is very important. That’s another transition that you have to make. Companies are, after all, all about people. The best people. How do you hire people? How do you learn how to hire people? How do you learn how to hire people outside of your expertise? If you are a technical founder like I was, you have to learn how to hire people, let’s say in sales, and marketing, and stuff.

These are some of the things that sometimes I had to learn the hard way. If you’re a non-founder, somebody else set the vision for the company. Somebody else decided what the company is going to do. Now, it’s you to blame. If that doesn’t go well, it’s your on us. Learning how to set that long-term roadmap on what the company is going to do is another thing that I had to learn. I had to build a strategy for doing that. That’s the strategy behind my companies.

Karan: Let’s talk about hiring because that’s a big topic for all of us here. We actually heard a lot of folks here had to let go of people in the last two years, and then now we’re starting to hire. You mentioned something that has always stuck with me, which is you are a technical founder, you’re a product architect, yet you were able to hire some amazing go-to-market talent in the Nutanix and Cohesity journey. I remember pulling some people that are your lieutenants and saying, “Okay, use some words to describe Mohit.” And they used to say, “Tough but fair. He’s a hard boss.” The way I interpret that is that you have never tolerated much less celebrated mediocrity in your organizations.

What are the things that you look for? When you’re hiring somebody, for example, a sales CRO in a company where you’ve never been a CRO before. What are the things you’re looking for as you hire somebody in that role?

Mohit Aron: I’ll lay it out as a generalization. First of all, great companies are built by great people. I’ll say that again. If you have an underperformer in a job, either you have to do the work for that person because the buck stops with you, and then you cannot scale. By the way, I will talk about repeatability again and again. It’s all about repeatability. We’ll get to that.

To hire, I literally came up with hiring strategy. The way I do it is for every role, I come up with what I call a list of competencies you need in the role. For instance, if you are hiring a, let’s say a sales leader, maybe you need the person to have done it before. Maybe the person should have been a VP of sales at a prior company and maybe for a number of years, and maybe the person should come from enterprise background. Whatever those competencies are. I split those competencies into what I call scorecards. Three scorecards. The first one is what I call a pre-interview scorecard. This is competencies you can figure out by looking at the person’s resume or by maybe doing a phone screen because I don’t want to waste time. There’s a lot of time that goes in interviewing people. I don’t want to waste time if the person doesn’t even meet the basic competencies. So, that’s a pre-interview scorecard.

Then the next one is what I call an interview scorecard. This is what is used. These are the competencies I’m going to test for when the person is interviewed. I don’t test all of them. Maybe, I’ll test three or four of them and then I’ll have other interviewers test the other ones. Collectively, we form a very data-driven full picture of the person.
The last one is what I call a reference check scorecard. These are the things that you ask when you do reference checks. Now in the absence of this, here are some of the mistakes people make. The first mistake people make is they will interview someone. They really like the person, the way the person speaks, the way the person moves. Basically, it’s a chemistry match. But please understand that chemistry match is only one of the competencies you need in a role. You may need some 10 other competencies. Ten other big rocks, if you may. You need to look for those. Unless you have them written down and unless you explicitly test for them, you’re going to make mistakes. Yet, another mistake people make when they do reference checks. Everyone knows reference checks are important, but here’s the big mistake people do. They’ll call up the reference, “Hey, is this a great person?”

The person says, “Yeah, this is a great person. Hire the person.” And that’s the absolute worst reference check you can do. Again, you need to lay out what you need to ask in a bunch of competencies. Maybe the first question is, “Would you hire this person again on a scale of 1 to 10?” Because 6 is a failure. It’s a failure mark. People hesitate giving a negative one. So if you push them to put a number at it, they’ll say 6 or 7. That’s really a fail. Unless it’s a 8 or 9, I would not hire the person. Similarly, did good performers in your company. Did they value this person? Then maybe if you want to validate some strengths, “Does the person have a good methodology in a day-to-day execution?” Something like that on a scale of 1 to 10. Everything is on a scale of 1 to 10. You start getting the real answers. For instance, if they say 8, you ask them, “So, why not a 9?”
Then they’ll say, “Well, there is this one occasion when they didn’t do well.” Then, you can poke into that. But if you just ask, “Is this a good guy?”

“Yeah.” That’s the absolute wrong reference check that you can do. This is the hiring strategy I use. It has significantly increased my probability of hiring good people, but I would say it’s not 100%. No hiring algorithm is 100%. Even if you hire a good person, they might be good at the time you hired them. Couple of years down the line, especially if your company is growing at 100% or whatever in three years, it’s 8X or something like that, the person may no longer be good. People feel really uncomfortable with this, but you have to performance-managent.

Karan: That’s great.

Mohit Aron: When you hear people saying that I’m tough, it’s when that person is not working out. I don’t want to make it a hire and fire culture, so there’s a period of time when I’m trying to uplevel with the person. And guess what? The person is in pain. My goal at that time is to either uplevel the person, it’s up or out for me. Either the person elevates himself or herself, or they’re going to be out. As simple as that. And there’s a time threshold I have for that. That’s it.

Otherwise, I will end up doing the work for the person. Or worse, nobody does the work and the company is not doing well.

Karan: One of the things I’ve always appreciated about the way you manage and lead, there’s a combination of autonomy and accountability that you held very tightly, and I think that’s worked really well. By the way, there’s a survey in all of your phones right now. On a scale of 1 to 10, would you take money from Madrona again? So, we’re going to follow up on that part later.

Let’s switch gears a little bit. Some of the companies here are well past product market fit, and at this point, are thinking about product market pricing fit after Madhavan’s talk. And some of them haven’t reached product market fit. I’ve asked this question to many entrepreneurs, I’ve thought about it myself. What does it actually take to say that we have product market fit? Is it a feeling? Is it a scientifically calculatable metric? How do you think about product market fit? When did you know you had it at Cohesity?

Mohit Aron: I’m a B2B person, building enterprise companies. I have a very crisp definition for a product market fit. Again, it goes back to repeatability, but here’s my definition. If an average salesperson, again, average is the key, not an elite salesperson. If an average salesperson can sell to an average customer, again, not an elite customer, an average customer without involving people in headquarters, without involving me, without involving my C-level staff, then you have a product market fit.

If you think about it, if it’s a average person, you cannot hire all A-players as salespeople, and average person needs to be able to sell your product. You cannot all have elite customers who understand your product. The rank-and-file customers are average. The average sales guy can sell to an average customer without involving headquarters, because If I’m getting involved in every deal, it’s not repeatable, it’s not scalable. Once you can do that, you suddenly have repeatability. It means that now, I can hire tons of salespeople and they can sell to tons of customers without putting a load on the headquarters, and now you have a product market fit.
That’s my definition of a product market fit. When big deals start coming without any involvement, without me even stepping into the headquarters of the customer, suddenly the gong goes off and some big deal happens, I know there’s a product market fit.

Karan: That’s great. By the way, if anybody has questions, just raise your hand. This doesn’t have to wait until the very end. I’m sure folks have questions for Mohit, then I’ll pause. Just make sure somebody tells me if somebody’s hands are risen.

All right, let’s move to one of the things that I observed about you is that one thing that you navigated really well is that when you pitch for money or when you pitch for your idea to employees and other prospects to hire them, there’s this constant battle between you have to be focused enough to get the right wedge in the market, but you also have to have a big vision to be able to excite people to really understand this is a 10 billion whatever company. It’s hard for founders to navigate it because you’re constantly getting the feedback, it’s too niche-y, or you’re getting the feedback that it’s too unfocused.

How did you navigate that? Cohesity, in some ways, has replaced multiple companies as a platform, but you didn’t pitch that, well, you did, but you didn’t raise money and you unraveled those layers of the onion as time went on. Walk us through how you navigated that challenge.

Mohit Aron: Absolutely. First of all, if you want to build a great company, the vision has to be big. If you have a small vision, even if you build the best product, that vision can be copied. Very soon, your product will be a commodity. But at the same time, when you have a big vision, you can’t wait tons of years to build that vision. Customers are not going to pay for the vision, they’re going to pay for the actual product. It’s very important to have in my mind two components.

One is a vision. The second is, what I hesitate using MVP. I don’t like minimum valuable product. I think Madhavan was also using minimal, I think, valuable product. I prefer a minimum lovable product. You need to have a very clearly defined minimum lovable product that you can actually sell to customers.

The bigger vision is useful, A, for hiring great employees because after all, they’re joining you on a mission. They don’t want to do some small thing and then there’s nothing more to do. Second, the bigger vision protects you against competitors. By the time they try to copy your minimum lovable product, you are traded on the vision and moved ahead. And third, it’s also important for the customers. They want to solve a problem right now, but they want to solve it in a way so that they can keep your product for years and you can add further value.

Having these two components is key to building a sustainable business. There’s plenty of companies that were flash in a pan, did well for a few years and then became a commodity. We can go on and on and on. They eventually had to shut down or got bought by someone for a small price. It’s basically the problem of not having that bigger vision. Or conversely, some companies only have a big vision but don’t have a very well-defined minimum level of product. Maybe you spoke about feature creep when Madhavan was here. Some of that stuff is lots of vision but no lovable product.

Karan: By the way, one of my favorite stories of Mohit and he’s too humble to admit to it, but he’s one of the best engineers in the Valley. Period. When I invested in Mohit in the Series B, it was pre-product, and I remember him pitching that he’s going to launch the GA. This GA product was pretty big but it was still that minimum lovable product of an even bigger vision. He said the product is going to be GA’d four months later. It was October. We were somewhere in June, July. He was like, “It’s going to be October 14th.”

I was like, “All right. Well, I’ll just add another three months to it,” because no product goes GA when the founder tells you that it’s going to go GA. And I remember calling him like a month into it, in the afternoon, and I asked his EA, “I want to talk to Mohit.” He’s like, “Oh, no. He doesn’t take calls between 1:30 and 4:30.” and I’m like, “What the hell? I just invested $20 million in this company.” It turns out that from 1:30 to 4:30 p.m., Mohit would put on headphones, and he would sit there and code. He wasn’t taking any calls from investors or customers or anything. October 14th was the launch day, you launched the GA product on October 15th. And we sold, what, a million bucks?

Mohit Aron: Yeah, in the 1st quarter itself. That day when we GA’d the product, one of the customers with whom we were doing alpha testing, he surprised me. He stood on the stage and said, “I’m going to buy it for 300K.” That blew our numbers right there, the target right there. More orders came the very first quarter. So the very 1st quarter, we actually surpassed a million dollars.

Karan: Now, you found product market fit. Your average salesperson is selling to an average customer an average product. What do you do after? What is the next thing you do as a CEO? You feel it, you’ve see it. You see it it’s happening. How do you change the operational cadence of the company right after you got product market fit?

Mohit Aron: Repeatability. I mean, the repeatability is a necessary condition for product market fit. I think the company needs to operate very differently when pre-repeatability or pre-product market fit. And very differently, post-product market fit.

Karan: You stopped coding for three hours with your headphones right after that.

Mohit Aron: So pre-product market fit, your job is to get to repeatability. Your job as a founder and the rest of your C-level suite is to get involved in anything that’s important and get it finished. My job was to finish that code pre-product market fit, get a solid. If there’s no repeatability, there’s no big business. Post-product market fit, the equation changes. By the way, pre-product market fit, your job is also to conserve capital. You’re trying to do more with less resources because you want to extend the runway, whatever.

Post-product market fit is actually a mistake to be conservative because now you have the product market fit, a lot of companies are watching you or a lot of competitors are watching you. They want to copy you, that sort of stuff. You want to press on the gas. Nobody should be able to surpass you or catch up to you. That’s also where delegation comes. Use as much leverage as possible. You hire for the right roles, you want to delegate responsibilities.

Pre-product market fit, my job is to finish anything that needs my attention. Post-product market fit, it’s to, A, delegate as much as possible. Look, you’re always going to have people who may not be able to do the job that they’re assigned. Your job is to be a symphony or kind of like a symphony orchestra player. I’m sorry, a symphony conductor, not an orchestra. But not an orchestra player. You’re a symphony conductor to oversee a lot of things. You take on a breadth roll rather than a depth role, and your job is to descend and parachute down in areas that may not be doing well with the goal of coming out quickly. What that means is either you replace the person who’s not able to do the job or train them. Or you bring it to a point where it’s going to operating at 80% efficiency, and now the team can take it onwards. Not to finish the thing because you’ve got to watch out for a bunch of other things.

It’s a very different mindset. You have to change that mindset. Once you attain product market fit, suddenly if you don’t change that mindset, you’re going to kill the company.

Karan: There’s a really good quote by Aaron Levie who said, maybe like 8, 9 years ago now. He said, “The job of a startup CEO is to do as many jobs as possible so the company can survive, and the job of a scale CEOs to do as few jobs so the company can survive.”

Mohit Aron: Yep, that’s right.

Karan: I think that articulates what you were saying really well.

Audience Question: I love this theme and so I’m curious. A correlator to that is that a lot of times, you’re kind of the hub spokes, and all the spokes come to you to solve the problem. What did you learn in terms of finding ways for the spokes to solve the problem so that everything didn’t have to go through you, the hub? That’s just not scalable, especially as you get bigger. I’m even thinking about it the right way as you upleveled yourself and tried to work with a very capable executive team and not have to solve every problem.

Mohit Aron: That’s a great point. Rule number one, when you bring a problem to me, I also want you to bring the solution to me even if the solution is wrong. I will not give you the solution otherwise. It’s too easy for them to just bank on you. You present the solution and you keep doing that, they become more and more dependent on you.
Even if the solution you bring is wrong, that’s okay, but you need to bring a solution. If you do that, very soon, you’ll realize that they’ll start solving problems themselves.

Karan: That’s excellent. I have to use that. We have to use that internally, too. Let’s switch a little bit to generative AI. You can’t go through any conference, any session, any meeting without talking about it. We’re seeing a lot of investments in the infrastructure layer and the model layer. What’s your view of where we are in AI today? What do you think the world believes about AI that you don’t think is true?

Mohit Aron: I have a balanced view on AI. On the positive side, I think it’s a mistake for any company to be ignoring AI. If you’re doing any company and you don’t have AI as a component within it, it’s probably a mistake. Every company needs to view AI seriously. AI is here to not just stay, but also change most businesses in a fundamental way. I think I’m not saying anything that is outlandish there. But on the other side, I also believe there’s a lot of AI-washing going on. Companies attach .AI in their domains and project themselves as AI companies when they really don’t have any deep AI in them. A lot of people I know who are basically doing nothing more than after the popularity of ChatGPT, they basically have some sort of a chatbot attached to their product, and they’re calling themselves an AI company. Or basically, they have some twist of RAG, retrieval-augmented generation, and they extract information in some way. They call it an AI product. So, there’s a lot of that going on.

Look, the fundamentals of doing companies has not changed. You need depth in your product. You need a significant competitive differentiator to be able to build a sustainable business. And even with AI, you need all of that. If you don’t have these things and you’re just slapping on AI in one of the ways I said, it’s not a real AI company, in my mind. There’s a lot of that going on. I think people know a lot of companies have come down, they raised funding at big valuations, calling themselves an AI company but then they couldn’t prove all of this, and their valuations came crashing down. So, that’s also happening. I think a lot of the negative returns, you see. I think back in the last two years, a lot of companies got funded at big valuations and then they couldn’t live up to the promise. And so, that’s also happening.
So, it’s a balanced view. I think it’s a huge tool that we have now at our hands to really push technology forward. It’s irresponsible to just throw the name AI out there and pretend that you’re an AI company when you’re not. So, the fundamentals of doing business have not changed.

Karan: Any more questions? Otherwise, I’ll keep going. Somebody there.

Audience Question: Thank you. When you talk about vision and minimal lovable product, that’s something I sometimes struggle with because some visions like Disney is to make the world a happier place or whatever it is, which is sort of ambiguous enough to pretty much play in any particular field. Then I hear other visions that are almost like the product on steroids. You know what I mean? It’s kind of like, “Our vision is to make the best banking software in the world,” which that doesn’t sound that awesome.

I’m curious about how you set the vision at the right altitude to not be, maybe, so broad and nebulous that no one really believes it but also not so narrow that it’s really just a supersized version of what your product already is.

Mohit Aron: Yeah, great question. I think the answer will come from asking what additional problems you can solve? Otherwise, it’s a big abstract thing or the best thing since sliced bread or whatever. It means nothing. So, your minimum lovable product is solving some problem for the customer. As you build on your vision, what additional problems are you solving for the customer? What additional things are you enabling for the customer? And if that is a growing thing, then you have a bigger vision, otherwise your vision statement doesn’t probably make any sense. You need to keep on adding incremental value, keep on adding that value to customers, and then you have a bigger and bigger vision.

Said another way — you better have a roadmap beyond your minimum lovable product. What’s the next thing you want to deliver? When you talk about that stuff, by the way, with customers and they see the additional value you’re going to bring, that’s when they buy your vision. Otherwise, all these buzzy words mean very little for the customers.

Karan: Mohit, you’ve managed to, obviously, build great companies, but you’ve also raised money with Tier 1 investors along the way. You’ve got Sequoia, Excel, ourselves, Battery, a whole bunch of venture investors that know you, that want to invest in you. As you think about picking investors, as you think about building a board, what are the things that you would advise the founders here as they’re going on to raise their follow-on rounds? And their first round, sometimes. What are the things that they should be optimizing for?

Mohit Aron: The first thing I would start by saying is be very clear on what you need from your investors and your board members. I’ll tell you what I look for. Number one, I look for investors and board members who will stick with the company in not just the highs. Everyone sticks through the highs. But what about the lows? Even in the highs, sometimes when the things are heading high, they’re like, “Oh, let’s make an exit. This is the time to get the money back.” When it’s a low, it’s like, “Oh my God, let’s sell the company before it gets too low.” So, do they have the stomach to stomach the lows? That’s number one for me.
Number two, you’re hopefully trying to build a company that will become much bigger later on, and this is not the only round of funding you’re raising. So, will this person be able to stand up to his or her partners in future rounds and thump his fist and say, “I believe in this company.” There’s always going to be naysayers who try to push back, “Hey, let’s not fund this company at this bigger valuation.”

Karan: Nonbelievers, yeah.

Mohit Aron: Yeah. So, can this person actually stand up and say, “No, I want to fund it again”? That’s a huge benefit. If you have one of your existing investors standing up in future rounds and saying that, “I believe in this company. I will put money again,” that’s a huge incentive for people who are non-investors right now to come write checks for you. That your existing investors believe in you so much.
In the absence of if a person doesn’t have that conviction, okay, now I’m left with my existing investors who are not standing up to say they want to invest. Why would another one invest, right? The key to raising big rounds, and I’ve raised some pretty big rounds, is that your existing investors have the cojones to stand behind you.

Karan: You had the quality problem of saying no to people more than most people.

Mohit Aron: Now, trust me. When you raise big rounds, everyone is jittery, right? That’s when the river meets the road. I thank Karan. Karan’s always been very good at that. He always fought his partners, “I’m going to put money behind.”

Karan: Took a lot of flack for that in the early days, but I think it worked out for everybody. There was a question there.

Audience Question: This intersection of vision and product market fit, like how you set the vision, you said something that I wanted to pick on, which is that you solve additional problems, especially as there’s fundamental technology shifts happening always but nowadays with AI. How do you think about existing workflows and tackling existing workflows versus new workflows as you’ve built multiple companies?

Mohit Aron: Yeah, great question. The first thing that you need to do, and this is one of the things I always do when I start companies, is you need to build a hypothesis of what it would take for the company to succeed. Haven’t you run into people who are, basically, running failed companies or failed products, failed companies, or the company has already failed or the product has already failed? You’ve said, “What were they thinking?” I could have told them that this is not going to succeed.

It’s actually amazingly true. I thought that why not move back to the time when you’re conceiving of the company and do that at that point. Literally, I have this framework where I write a hypothesis. It consists of four parts. The first one, the first section, the first part is elevator pitch. If I literally run into my prospective customer in an elevator, in five minutes, how am I going to convince that person? Number one, it needs to be a real problem that the customer cares about. Number two, I need to have a solution that solves the problem in a good way. Number three, the product needs to be differentiated. These are the key components of an elevator pitch. That’s section one.

Number two is that minimum lovable product. What does it look like? The fact that the Fire Phone was what it was because they didn’t have a crisp definition of a minimal lovable product is. They kept throwing features. You need to have a very crisp definition of a minimum lovable product. Number three is why would the company succeed? What are the trends that are helping you? Number four is why would it not succeed? What would a naysayers say? What technology shifts might happen in the future that would disrupt this? You are to rebuttal against each of them. And then, you write this hypothesis. I literally do it for every one of my companies. I share it because I might be drinking my own Kool-Aid. I share it with people who are objective and knowledgeable. If they say, “Okay, this is a solid hypothesis,” then I have a company.
What I’m trying to tell you is that upfront, I’ve thought about these shifts. I remember Doug Leone from Sequoia, he asked me when we did Nutanix. After Nutanix achieved the product market fit, he asked me, “What has changed since your initial vision?”

I’m like, “Zero. Nothing.” Cohesity, I shared my initial deck that I used to raise my Series A funding with some of my employees. They were surprised to see that 10 years later, we are basically building on the vision that I said 10 years earlier.

Karan: That’s great, yep.

Mohit Aron: These things are thought upfront. Now, there are some shifts that are going to happen that you can’t foresee, and that’s where you put your best friends together. You collaborate with them and then you align that, “Okay, this is how the vision needs to shift to accommodate for these technological shifts.” And if you do that, basically what I’m going to say is that you not only have a hypothesis at the beginning, you also keep building and improving this hypothesis as the company goes long. I think you have a fair chance of building and foreseeing upfront these technological shifts that might come and interrupt what you’re doing, and then navigate around them.

Karan: We’re almost out of time. I have one last question for you. I’m a fan of Patrick O’Shaughnessy. I don’t know if you’ve listened to his podcast Invest Like the Best. I know Matt does, and I do. He ends all his podcasts with a question that I love, so I’m going to ask you that, which is what is the kindest thing that anyone’s ever done for you?

Mohit Aron: Look, I’m blessed. You don’t get here without kind things being done to you. I think if I may pick a few, the kindest things that people have done to me is when nobody believed when I was in a tough spot, the few kind words that were said meant a lot at that time. Of course, when the going gets tough and I’m having a hard time raising funding, when there are some backers like Karen who backed me when things were tough, that’s very kind.

So look, you make mistakes, you fall down, you get up again, you run again. When you fall down, who’s there to actually show you kindness is what matters.

Karan: Thank you for that. Thank you for the kind words. Thank you for your partnership. Thank you for your leadership. Most importantly, thank you for your friendship over 15 years. Thanks for being here today.

Mohit Aron: Thank you for having me here.

Listen on Spotify, Apple, and Amazon | Watch on YouTube

Terray Therapeutics CEO Jacob Berlin returns to Founded & Funded after three years to share how the company has scaled from an ambitious startup to an industry leader in AI-driven biotech. Learn how Terray’s proprietary hardware, combined with the world’s largest chemistry data set, is powering new discoveries in small molecule drug development.

Jacob also discusses how the company’s $120M Series B fundraise will prepare their internal programs for clinical trials and further enhance their AI platform. He shares insights on where he sees the future of AI and drug design and dives into how founders can balance internal innovation and high-profile partnerships.

Don’t miss this deep dive into the intersection of AI, biotech, and innovation!

---

This transcript was automatically generated and edited for clarity.

Jacob: Thanks, Chris. Super fun to be back here. It’s pretty wild that it’s been three years and everything that’s gone on, and I’m super excited to be back and talk about Terray some more. One of my favorite topics.

Chris: So, since it’s been a while, can you give me the brief overview and maybe even the elevator pitch of what Terray does and what’s happened since then?

Jacob: Absolutely. Terray is a biotech company focused on autoimmune disorders and immunology down in Los Angeles. We bring our unique proprietary hardware and experimentation to enable AI-driven small molecule drug discovery in a way that’s impossible without it. We’re deploying it for that internal pipeline on autoimmune disorders and also for our partners across a range of indications.

Chris: That was a good elevator pitch. It’s succinct. Before we get into everything, you mentioned small molecules there a couple of times. Could you explain why small molecules and why that’s an important thing to be working on?

Jacob: Small molecules would be the medicines that you’re probably all most familiar with, the pills in your bottle that you can take by mouth, you can carry them around when you go travel, and probably some of the oldest types of remedies available to humans. At this point in time, there have been incredible advances such that there are other classes. We now call those small molecules because there are large molecules, which are typically antibody-type therapies or protein-type therapies, so large molecules are typically made by biology or analogous to biology. Then there are, of course, also cellular therapies, genetic therapies, and others on the scene. For us, we’re exclusively focused on small molecule therapies which remain the world’s most abundant, most impactful medicines. There are a lot of opportunities still to develop new and better medicines in that area.

Chris: I think about it as if, for most cases, if you could develop a small molecule therapy for something that worked equally well, not all cases, but for many, it’s better for patients and very impactful to have your medicine delivered in that form factor.

Jacob: 100%. All of the different forms of therapy that bring relief are incredible, but they do have really different levels of complexity in terms of manufacturing, distribution, and investment to do it. You can see it today, for example, in genetic medicines, which are really amazing, like lifelong cures to previously uncurable diseases, but they take many months per patient to do and millions of dollars in cost. Although that one in particular, I don’t know if you can make a small molecule analog to, you can see that as you move down to a pill that you can carry in your pocket and take for your disease while you travel the world and go out with friends, that’s obviously an advantage modality provided that’s safe and effective. I do think they remain the medicine of choice when you can make them.

Chris: There’s a funny story that I wasn’t planning on sharing, but I’m going to share, which is something that you shared with everybody when you last came and spoke to Madrona to give the update, which I think was close to a year ago now, and we were working through the pitch deck and talking about how the Series B was going to go. I remember this special appendix that you brought, and it was basically — here’s where we were, and here’s where we are. The “where we were page” had one chart with a couple of dots, and that was it. The “where we are now” page had, I don’t know, as many dots as you could fit in while still making a legible, and that was just a sub-sample. That explains a lot of just the amount of scale that you’ve put into this company since then.

Jacob: Yes, it’s really incredible. When we came and chatted last time three years ago, by the way, we count zero measurements the way we count today because the first three and a half years of the company were about taking that experimental innovation, the proprietary hardware from an academic invention where my co-founder, Kathleen Elison, was pushing buttons on the syringe pump. We were doing one microarray a week, and it was all artisanal, and we’d measure 32 million measurements maybe that week, which was a lot. It was huge. It’s way more than I’ve ever done in my career, but nothing like what we do today. When I last came in, we were at that moment where we had industrialized it, and we had this incredible array of automated systems both making and using those arrays and measuring those data sets, following up and making molecules to put into downstream assays and following them through the drug development pipeline.

We were, at that moment, though, at the beginning of our pipeline journey and the beginning of our AI journey because we didn’t yet have the data set to drive those two. In the last three years, I say zero because we had made, of course, many, many measurements before that day, but that was the day that we locked to a consistent format, and there’s a bunch of needy technical details that nobody needs to know about, nor will I tell you to go into what we decided to do with certain elements of the science on the chip. But once we locked it, now we’ve measured over 150 billion raw measurements on the interaction side, which mapped to 5 billion unique measurements because every data point that we use in our modeling, we measure about 30 times and replicate to make sure it’s a high quality, precise data point.

In the intervening three years, we’ve made 5 billion unique measurements, which has led us to build then unique generative AI tools to design small molecules. That, most importantly, led us to then really move our pipeline and move our partnership work. We’ve realized a whole number of significant milestones between here and there. Looking back is always, I don’t know, shocking, exciting, terrifying for a founder. You look back at the old deck, and you’re like, “I’m so glad somebody funded that. We’re doing a lot better today.” And that one’s true. Looking back at what you all backed in the beginning, it was very much the vision and the core of what we do, but the realization’s come in the last few years. It’s been exciting.

Chris: It’s a fun one for me to think back on because the first time we met in person was a couple of weeks before the COVID shutdown. And since then, even dealing with that, it’s just a different company. It’s fun to be able to have this conversation when you’re now much more of a scaled-up founder leader of a company. You’ve learned a lot of these lessons, and so I want to jump into some of those. Since you mentioned, and we’ve talked about it a couple of times, one of the major milestones that you recently hit over the summer and announced in the early fall was this large $120 million series B fundraise. We’re all super excited about that. I think it’s a pivotal moment for the company, but I’d love for you to share a quick overview of what that is going to get for you. That’s a lot of money. People think biotech companies raise a lot of money. You’ve got big plans for it. I’m curious just what exactly will that enable?

Jacob: It’s really incredible. I think all the founders out there know the saying, “The first dollar you raise is the hardest.” I think that is still true, but the markets have certainly been, as I think everyone involved with biotech knows, a little bit bumpy. Maybe all times are interesting to start a company, but we started it right before COVID, ran into all their operational challenges like that you mentioned, and then maybe one of the greater boom markets for biotech funding and progress and then one of the greater devastatingly bear markets that followed on the heels of that. We’ve stayed really focused on execution from day one through all of that and into today. We’re really excited because my life’s mission has been to cure somebody for decades now, and we’re finally coming up on that. Owing to the nature of the market, we’re probably not going to cure one person. We’ll probably cure many, many people hopefully.

This money is so important to us because we’ll be bringing our first programs into the clinic from the first wave of targets we worked on, one of the unique aspects of the scale of the integration of experimentation and computations that we can work on far, far more targets than your average biotech company of our scale and then pick out the best opportunities and move those forward. We have the first couple of those headed into the clinic out of what we call our first wave of targets. We have a second wave of targets behind that that we’re also super excited about, and we’re continuing to invest in the platform as well, both for our own pipeline progression, like those programs, which I should note everything internal is in autoimmune disorders and immunology, but also delivering for our partners.

When you think about the milestones from three years ago to today, not only did we industrialize the technology, generate the data, and build these AI tools, but we moved those first programs of our own toward the clinic, and now we’ll move into the clinic. We started to build the second wave and all the programs behind it, and we saw scale in partnerships with Calico and BMS. Now we have a co-development deal with Odyssey, which is another exciting opportunity for us to use our technology advantage to really deliver medicines that matter. And then, as you know, just recently, we signed a deal with Gilead to bring the same approach forward and solve really challenging problems for them. We’re really excited to become the AI-driven small molecule provider of choice for large pharma, and it’s been incredibly gratifying to see that. We’re going to continue to invest in the platform and be best in class at the intersection of large-scale, precise iterative experimentation and AI, but also super excited. The primary piece is moving that pipeline into the clinic.

Chris: It’s the partnership velocity since you started to sign these partners or go after them has been pretty incredible. We’ll get back to that because that is a hot topic for companies across the board. Something you mentioned I think is also a hot topic, which is this platform versus product debate that seems to rage on a cyclical basis and biotech investing, whether it’s coming from the investors or the companies and Terray is very much building a platform. I mean, we certainly have lots of products, but there is a big platform vision there. I think it would be great for you to talk for a second about what being a platform means in biotech, why you have conviction in that approach, and why you think for Terray that’s the right path to take.

Jacob: It is probably one of the existential and repetitive questions in our industry. Are you platform? Are you asset? And the market certainly moves back and forth with its own opinions about which one is in and out, but I think for us, we’ve always been drawn to trying to solve the problems that are unsolvable and really transforming the cost, the speed, but most importantly by far the success rate of small molecules in development. I think probably almost everybody out there knows drug discovery is really hard, that with all of the incredible expertise and all of the tools that are available today, the failure rate even after reaching the clinic is the vast majority of molecules. That doesn’t count needing to go from the idea to the clinic. Overall, it’s clearly a very, very hard problem. It has an urgent need always for better approaches that give you a transformative opportunity to bend the whole curve and transform what can really be done out there.

For us, we came at it from that macro, good for the world, good for value, good for our science approach, and have been a platform company since day one. The core innovation was transforming how you measure chemistry, which then let us transform what you can do on the AI compute side. We faced the same tensions though because our product is not, our microarray chips, it’s not our AI model, it is the molecules. The back end of it is, of course, assets, the molecules themselves, and as they move through, and as you know, and probably many listeners know, the market has moved towards the asset world, move towards the clinic, but that’s why we do the partnership work. It’s why we have a diversified internal pipeline. We feel very strongly that the right way to monetize, realize value and deliver maximum impact from a platform is to basically translate it into as many assets as is possible, leveraging both private capital but also partner capital and partner resources to move multiple programs across different opportunities.

There’s room for both. There’s a lot of patience and need that you can address either by working off of a singular item and finding a clever way to do it. But also I think there’s a lot of room for transformative new approaches. I think you see that right now. Obviously, AI-driven small molecules and large molecules have been a huge topic of interest because they offer the opportunity to really transform success rates, which would be worth millions of lives and billions and trillions of dollars. Goodness knows if you really can change the whole thing.

Chris: One thing you mentioned in there, which involves this platform strategy, and you’ve mentioned to me really since day one, is creating a long-term company versus something that, “Oh, you can build an asset maybe for three to five years, and that’s going to look really great for a pharma to go acquire.” Either I made this up or you said it to me, but I remember asking you, “Hey, what are you going to be doing 10, or15 years from now?” Your answer was running Terray. I think that’s a great answer, but it’s a lot about how you’ve thought about the vision, what you’re building, and where this can go on a true long-term perspective.

Jacob: I guess this comes from the quintessential entrepreneur too naive to know you’re wrong type plan. I’m eyes wide open that the number of new biotech companies that transition to full-fledged commercial scale pharma companies is, I don’t know, one a decade, one every couple decades, but I really think Terray can be that one. We’ve always been focused on returning, now I sound like a broken record, but maximal impact to patients and of course maximum value that comes with that. That’s always seemed to me to be realizing the inherent advantage of the platform at scale and bringing those medicines all the way through, which means building the whole thing.

Obviously, in our industry along the way, sometimes people show up and make offers that everyone says yes to, but I think you’ve got a plan for the stuff you can control and plan for the strategy that you can execute by yourself and plan for the strategy that you think overall is most valuable and most successful. For us, literally since day zero, that’s been we’re going to make and sell our own medicines one day, a whole bunch of them, and we’re going to change the way the world does this, and we’re part of the way along that journey now, which is really exciting, but we still have a long way to go. As in our industry, the timelines and capital costs and scientific risk and discovery and development remain large, but we put ourselves in a position to execute it now.

Chris: I’ll say for me, it’s super fun to be able to work with a team like Terray and you and Eli, your co-founder, because of that true long-term view. It’s really differentiating. We’ll get back to a couple of your thoughts on the business-building side of this, but I think it’s a good time to take a nice detour or deep dive into the AI and the science that’s going on here. Given I think it’s the hottest topic in biotech right now, maybe besides the GLP-1 obesity drugs, we’ve got to talk a little bit about the AI that you’ve built. You said this before, but I think it’s really interesting. The AI came a little bit after the data generation came, but since then you’ve built a ton of it. I’m curious how you think the small molecule AI world is different than the protein design world or the antibody world and what you’ve done internally to build out this AI infrastructure.

Jacob: Now you’ve wandered into my favorite topics, although I love talking about everything. I can’t resist my origin story, anything science, risk, sending me down the rabbit hole for the rest of the podcast. Come for the AI discussion, stay for the enantiomer discussion that follows in the organic chemistry section. In all seriousness, it really follows the data. I say this a lot, but I think about the world as AI is transformative when it rests on top of the right type of data, which I think are those three pillars, large, precise, iterative. In every case where that data comes about and is transformative, it rests on top of hardware innovation that compresses the cycle time, transforms the cost exponentially and allows you to realize it. The one out there in the world that’s easy to pattern match to is digital photography.

You go from old photography, where you probably never have enough images to build DALL-E or Sora or any of these tools or facial recognition, to digital photography. Now, there are millions and billions of images and you can train the models and retrain them and refine them. As people probably talk about other podcasts, you teach what a cat is, and you teach you what a dog is, and you need all the images to train it into which one’s a cat, which one’s a dog before you then go ask it for like, “I’d love a picture of my kids cuddled up with a bunch of cats.” Now it knows, and it makes you a picture. The same problem exists in our space. That’s why I did my postdoctoral work. It’s why I ran the lab. It’s why I started Terray, which is that chemistry data is hard to get.

And traditionally it was me and people like me making molecules and putting them in a flask or putting them on a 96 well plate or 1536, yes, they know they’re different well formats, and measuring them and it just is slow. It takes a lot of time to make those molecules. There’s some interesting automation chemistry approaches to it, but mostly that problems remain very stubborn. Making molecules at scale and putting them into assays is still pretty slow and still pretty expensive. Where AI has come into our world, it’s come into where there have been curated high-quality data sets like AlphaFold of course, where the government fortunately curated a large crystallography database, but also there’s an enormous sequencing database that came about thanks to next-generation sequencing and the plunging price of sequencing and the time taken to do it.

That’s done transformative things for AI around protein design, obviously, protein folding large molecule design, and I think that’s why you’ve seen AI be most successful in biotech, first in large molecules. The question we’re tackling is, “Great, now I want to put a small molecule in there.” That data set has been smaller. The entirety of public data, there is maybe a hundred million measurements spread across a variety of different assays. We’re really convinced that the unlock for AI there is the data, the measurement of small molecules interacting with proteins at a large enough set and across enough targets and enough molecules to build generalized models that can solve these problems quickly and go work for humans that couldn’t before.

That’s what we’ve been after and that’s why the sequence we always knew our data would fit with, back then we called it ML, but now we call it ML AI. We always knew it would fit with these large computational approaches because we generate too much data. We generated 5 billion data points in the last three years. What human is going to flip through that and do anything? But what to build? We needed to get the data in first, and now we’ve been able to build really transformative tools, the first of which was COATI, which actually doesn’t depend on the data. It’s the large language model of chemistry that we built such that we can work with our data in a computational way and smoothly traverse chemical space to optimize molecules.

Chris: Can you explain exactly what COATI unlocks, maybe what it is, and then what it unlocks for doing AI in this world?

Jacob: Oh yeah, that’s an easy one because COATI is a South American raccoon, so I think that pretty much wraps it up. But no, in all seriousness, in addition to being a South American raccoon, it is our large language model of chemistry. For any of these AI applications, you need basically a mathematical space within which the optimization is taking place, but you need to take the real thing that you want at the end and convert it into math, if you will. That’s what COATI does for chemical structures. Chemical structures can be represented in a variety of ways. One is as a three-dimensional object, which is probably the closest to what’s really going on out there in the body in the world. That’s a series of atoms and bonds that make a three-dimensional shape, but they can also be written down in abbreviated notation like a word.

You can write them down as both and people use them interchangeably in different applications in our industry, but neither of those is a math representation. What COATI did was it’s a contrast optimization where you train on those two to build a common math language that can translate back and forth between either of those. I think of it as like a chemistry map where it’s basically mapping how similar or different molecules are in a math space so that if you optimize within that space and move close by, the molecule looks similar, and if you go far away, it looks dissimilar.

Getting that right took a lot of work and the team did an incredible job. It was published recently, it was on the cover of JCIM, and we open-sourced the first version for people to work with it. It’s done tremendous things for how you can translate structures back and forth into math and then move around to optimize. That’s just the first building. If the data’s the foundation, the COATI large language model is the next piece that allows you to traverse, but then you need the AI module, if you will, that will combine those two and move around and solve the problem after solving.

Chris: What’s interesting to me is you haven’t been able to take off-the-shelf machine learning or AI tools. There’s some of them in the workflows and say, “Hey, go to work on our data. You’re going to get great molecules out of this.” You’ve built this whole AI infrastructure, including the data infrastructure from scratch alongside some partners like Snowflake and NVIDIA who have been part of this conversation. I’m curious how you think about the reasoning for doing that and why we’ve had to build all of the models internally and what that does for our scientists.

Jacob: It’s been an incredible journey and one that, I don’t know if when we started, we knew how much of each of them we would do. This part’s always stressful. There’s so many people that have gone into making that possible. Narbe, who’s our CTO has been a driver, John and the entire ML team, Kevin, the whole data team. Because as you mentioned, you have to first be able to get at the data. Our workflow is very custom. We obviously have invented proprietary hardware. The way we read it is with imaging, and so we generate over 50 terabytes of images a day that we need to convert into the numerical values that we’re going to use to drive the models. That was a whole process that we built from scratch because nobody else made exactly what we made, and nobody processed it like we needed to process it.

Obviously, we stand on the shoulders of giants like all scientists, and there was stuff we borrowed from, but we built our own because we needed to be able to do that really quickly and efficiently. We work with AWS and Snowflake because we generated a data set the world hadn’t seen before in the early years of Terray. We want to not invent stuff. We want to use stuff off the shelf that’s cheap and works and does what we need and move on to other hard problems. But when we showed up to vendors and we’re like, “Hey, we have 5 billion measurements coming up soon, can we put them into your stuff?” They said, “Chemistry measurements?” And we’re like, “Yeah.” They’re like, “Ooh, no, that’s a lot.”

We worked with instead, on the flip side, like Snowflake, which is obviously a service built for data sets that large. We saw the same thing with the foundation model of chemistry. We tried every model that was available out there, and we found that when we applied them and use the power of our unique data set to ask, are these models really then connecting molecules the way we want to connect them for optimization? We got some suggestions we didn’t think were that reasonable, and I think we’ll come to this, but it’s one of the real keys of having expert humans in the loop when you build and use these models, because they were answers that our medicinal chemistry teams were immediately like, no way. This is off. It’s a rocker, it’s way off.

We had to go build something that constrained it and gave answers that made sense and really allowed us to optimize molecules. The same has happened with the generative side of the AI problem. The team’s done incredible work building all the way from the ground up, from the data processing through the foundation model of chemistry to the generative and predictive models that go into designing molecules to solve the problems. We built it all because we couldn’t find what we wanted out there.

Chris: It’s interesting. I joke and we’ve joked before, biotech companies are obviously not software companies in many senses, but on the other hand, you’ve pretty much built an entire software company from the bare metal infrastructure up within a biotech company, and it’s about equal to size of the science that is going on. It’s a fascinating change in how companies are built.

Jacob: We use as our slogan, everything small molecule discovery should be, and we picked it intentionally because we feel really strongly that you can’t anymore be all one thing, that you’re at a huge disadvantage if you’re only compute or only traditional discovery. Our intersection is of compute, so AI ML software, so that’s a huge piece of the business building all of that, but also the experimental side. We have a huge investment in build and robotics automation, large-scale data with precision, the iterates now, like I said, I repeat myself a bunch, but it goes then in the service of the pipeline and the preclinical development.

We still have the teams that you would identify anywhere else, Medcam, your biological assays, and everything else that goes into that cell assays. I think you need all of the teams working really closely together. The last piece is that we also essentially have a little mini manufacturing business in that we make our microarray, proprietary microarray technology by assembling a variety of different things and building our custom libraries in-house. We have four businesses under the hood at Terray, but they all go together to drive the one singular value driver, which is the outcomes. I don’t think you can do just one of them and be successful in the way that we are.

Chris: I tell people at Madrona all the time, and other people, if they find themselves in East LA, they should visit Terray because it’s just visually so striking, the amount of automation, hardware innovation, and robotics that it’s just there and required. Every time I go and take a peek, it blows me away. I know we’ve seen that with when the New York Times visited, for example, and other investors, you have to see it to believe it.

Jacob: It is really different. As my brother Eli and co-founder advertises it, it’s not just a lab tour, although it is just a lab tour, but it’s an awesome lab and it’s one of the other milestones. Since three years ago, we’ve really lived the startup physical footprint journey. It’s been incredible in that same look back, we started the company in a local incubator at a shared bench and a shared essentially closet that we did our imaging in. Last time we did the podcast, we had moved from there and matured into a step-up space and we were working in a couple suites in a shared building, but we’ve been really fortunate since then that we moved into a, 50,000 square foot headquarters in Northeast LA, Monrovia for those in the know, great spot. And we’ve really then been able to build our workflows the way we wanted into the physical footprint of the building.

If you come to Terray, or our partners or the New York Times, or others, you have seen this whole first floor where the automated imaging and liquid handling systems are running to use these little microwave chips and make them millions and billions and billions of measurements all in a way, like a whole field of them. It is strikingly different. The interesting thing is that upstairs then looks in many ways, like a canonical biotech drug discovery company, although with a lot more robots in the hoods than on average. You can see and almost feel how the pieces fit together and work together, except perhaps as we talked about for the AI piece where you just see really smart people working at computers, but you see the impact as you move upstairs and downstairs and see the molecules that are being made and tested. It’s pretty incredible watching it all come together. I encourage anyone who’s interested to reach out and let me know. We’d love to show people what we’re doing at Terray.

Chris: It’s a pretty great tour. I’m lucky I get to go all the time, but it’s pretty fun. I want to get into a couple of your business theses and lessons you have to share. But before that, circling back to the AI side, I think one of the things that Terray is really good at doing is predicting completely de novo structures. And so when I say that, I contrast that toward a bunch of other AI platforms, which are very good at predicting things, especially binding molecules, but they look 99% similar to known binding molecules. That’s impressive in itself, but it’s very different than how you’ve approached the problem and how you think about this pure de novo or unrelated structural prediction. Talk a little bit about why that’s hard and why you think that’s also the way forward.

Jacob: It’s interesting. In my mind, this one connects back to the platform versus asset question in the same way that there’s value to a company being wholly invested in one medicine and bringing it through and being successful. There’s value to patients and to the ecosystems, to taking previously known molecules that either do work or almost work for something and making them better. There are innumerable examples of that, including the statins. Everyone knows and we’re taking, it wasn’t the very first one that became the most ubiquitous. There was refineman and the most ubiquitous one was an optimized version thereof. Those are exciting problems and problems that we can tackle. But I think the most exciting and the biggest benefit for both human health as well as value is solving the problems that just can’t be solved out there. That’s like, as you mentioned, would be what we call de novo where nobody knows where the molecule is or what it looks like.

It’s out there in COATI’s chemical space mapping somewhere, but goodness knows. The key then is to be able to do your own measurement to get a starting toehold where there wasn’t data before. As I talked about, AI always needs data. I don’t think it’s any surprise that AI’s first impact on small molecule design has been predominantly working in areas where there was already data, working around known molecules, patents, things that were out there and making better versions of those, which again, are very valuable, have impact and are also honestly often much quicker to bring to the clinic because of the path that’s been trod before you. We work on a different approach, which is to bring us your hardest thing. I think this is why you see the partnerships with large pharma because they’re bringing us of course, the things that they can’t do themselves otherwise they do them.

We’re out there working on very hard things where often there is no known starting point. We do this for our internal programs as well. For us, that’s why we use our sequential iterative process where we use our platform to measure very, very, very broadly across chemical space, 75 million plus molecules, but we’re obviously chemical space, infinite. We’re very sparsely sampling, looking for a starting point, where can we possibly get going on this? And that gets you going on the de novo, but it doesn’t possibly give you enough data for the model to be impactful. We followed that with a design and test cycle where we then build a new library of millions of molecules around that area of interest such that we massively enrich the models with a lot of local knowledge around the area where we do know now that there’s an answer in there.

That sequential build lets the model both broadly understand chemical space, what doesn’t work mostly, and then enrich into what does work and become essentially like a AI co-pilot for the Medcam team where they’re able to ask it questions as they go about their work and think about, “Hey, I need this molecule with these improved properties, where should we go?” I’m super excited about it. As you can tell, there’s nothing more exciting than finding a totally new answer to a intractable science and health problem. I think our approach really gets it done.

Chris: I know that you’ve now found many of those molecules because I get to see the outputs of that not in real time, but on a regular basis. It’s impressive how that’s been able to occur with all the work that you’ve done. I have two more questions for you, both are more on the business side and the business philosophy. Now that it’s three years in, I would say you’re an experienced founder.

Jacob: Three years since the last podcast.

Chris: That’s true.

Jacob: Six plus total. I’m a deep expert now.

Chris: That’s right. You’re a very experienced founder. I mean, you’ve scaled the company a bunch since the last time we talked. I want to hit two things. On the business side, Terray’s always been about the partnerships as well as the pipeline. I am curious how you think about this strategy because there are a lot of companies that will only focus on their internal pipeline and that’s not how you approach the business strategy.

Jacob: This also goes to the platform build question. I was influenced by an article I read long time ago looking at expected returns across numbers of assets. Back then I think the conclusion of that particular analysis was like, well, if you have 20 programs in the clinic that are appropriately sized to their market and whatnot, you’ll positively return over them. Of course, you see the real world version of this large pharma is a successful profitable industry that makes many bets, but in part also does it through acquisition and letting the bets play out outside of their ecosystem. If you can resource enough thoughtful bets, you’re likely to be overall successful. The inverse of that, as we certainly know, that one singular bet actually is odds on to lose.
As you know, I’m a baseball fan and so I talk about this a lot is sequence luck. One team, all their hits come together, they score a bunch of runs. The other team only gets one every inning, they lose. And then one, I’m a boss, I just like to point out one team sometimes also drops the ball for an entire inning and blows the World Series, but that happens. Coming back to what we’re talking about, we work with partners because I mean, it would be great if you guys would give us a few billion dollars and then we would resource all of our own programs, but that just hasn’t worked out yet.

Chris: Someday.

Jacob: Partners give us both. They give us the opportunity to resource more programs than we otherwise could through their capital commitment, not only in what they pay us to do the partnership, but the fact that they’re going to then carry the backend development of those molecules through the clinic and out to patients. We have an opportunity to realize value where we otherwise wouldn’t reach patients. The other piece is that it also realizes expertise. Internally, we were fully on immunology and autoimmune disorders, but with our partners, we touch a variety of other therapeutic areas that would’ve been a whole another build for the company to move into those types of indications.

It’s a way to realize the promise and value of the platform while you’re still a smaller company and be capital-efficient as you build and grow, tilt the odds of overall success in your favor from a singular coin flip, if you will, although the coins from very negatively weighted in biotech, to an ensemble approach that starts to give you a leg up on sequence luck. If you do seven programs and the first two fail and the last five succeed, that’d be incredible. That’d be the biggest home run ever. You might not get to do the last five if you only have the first two bets. This is a way to do them all at the same time, do them with really expert, wonderful partners who are just well-resourced and well experienced to be successful at the programs we do with them. So yeah, it’s always been both for us.

Chris: That’s really well put. Finally, I want to ask you about one of my favorite parts of Terray, which is the very unique and extremely high-performance culture you’ve built, and you’ve set an incredibly high bar just to get a job at Terray. I can think of one time, maybe in the last four years since I’ve been deeply involved, it is actually, I guess, closer to five now, since I’ve been deeply involved in the company when we’ve lost anybody, or we’ve lost someone, we’re even like, “Oh man, that was really terrible that we lost that person.” How have you done that?

Jacob: It’s really remarkable to me because as opposed to some of my friends and colleagues in other markets, it’s not one of the things I worry about when I go to work very much. It’s like, oh, we’re unexpectedly going to have a large churn in the company. We’ve been really fortunate to work with wonderful people including yourselves and the rest of in the investing ecosystem too. It’s really remarkable to me how mission-aligned everybody involved with Terray is. I’ve always been, as you probably can feel through this, super mission-driven, I’m here to make the world a better place and this is how I want to do it. I think that shines through as we hire people and build the team. It’s been one of the most incredible parts of this last journey because the other piece of the milestones is last time we talked, the company must have been four times smaller, and we’ve been through that growth and maintained, as you noted, the quality people we want, intensity.

It’ll sound cliche, but it’s because we hire for the person and the culture and the way we work together, not necessarily just for the skillset, which does make our searches take forever. We talk about this all the time. The trade is always time, because you can find the person who not only does what you want, but also does it how you want to do it. It’s going to take if you hold to both bars. There are times when that’s really tough, and it’s like, we really need somebody, but overall, we’re always happier and more successful when we get both. We’ve built an interview for that since the beginning. As we’ve talked about, I’m not a huge fan of just canonical words for values like, “Oh, we’re about excellence.” Of course, we are. So is everybody else. I hope. Otherwise, I don’t know what you’re doing. We’re really focused on how we work with each other and the operating principles, how we communicate with each other, how we make decisions, how we treat each other.

It’s been just a real joy to watch that cascade down through the teams. I have a little rotating lunch I do across the company, like three or four people every week just to say hi. It’s explicitly non-work, they just get to hear my awesome baseball jokes and thoughts about movies and TV and whatnot. One of the new employees was there, and I was like, “Oh, how’d you find Terray?” They’re like, “Oh, well, my friend who used to work here. She left for a school opportunity.” That was awesome for her. Was like, “You got to work at Terray. It’s awesome.” And nothing makes me happier. The science part obviously motivates me. I love science still. I’ll go back and tell you more about organic chemistry if you’d like, but the building and the people side is every bit and maybe even more gratifying to see such a wonderful teamwork together. I don’t know what the secret is except not making compromises on that aspect. There’s never anybody who’s good enough that you’re willing to compromise how you want to do it.

Chris: Well, I can’t think of a better place to end the discussion on that note about amazing people. You are one of them. It’s been really fun to work together and I really appreciate you joining me three years later for this discussion.

Jacob: Well, I appreciate it, Chris. Not only the awesome conversation today, but as you know, you guys have been convicted supporters of our work from the beginning, and it’s not that easy to find people who want to take the big, big bet and go for the whole journey. It means a lot to me and the conversation we just had, you guys have been mission aligned and how we want to work together aligned from the beginning. So appreciate it. So excited to be back, and thank you so much.

Chris: Thank you.

Listen on Spotify, Apple, and Amazon | Watch on YouTube

Imagine a future where healthcare isn’t just reactive but deeply personalized — where every patient gets the right treatment at the right time based on a precise understanding of their biology. This is the future Ovation is building, and on this week’s Founded & Funded, Madrona Partner Chris Picardo dives into it all with Ovation CEO Curt Medeiros.

From transforming underutilized clinical data into rich multiomics datasets to forging industry-leading partnerships with companies like Illumina, Curt shares how Ovation is shaping the future of precision medicine. He also opens up about the challenges of building a scalable, privacy-first platform, the lessons he’s brought from leading large healthcare businesses, and why collaboration and diversity are key to solving complex problems in healthcare.

This transcript was automatically generated and edited for clarity.

Curt: Thanks for having me on, Chris.

Chris: Yeah, thanks for being on. This is really fun. I think it would be great for everybody. If you could just do a little bit of a reintroduction to Ovation. Why was the company created? What’s the role in precision medicine and data innovation? And how do you think about Ovation in this emerging data world?

Curt: Absolutely.

So, the founders put together Ovation with a simple concept. There’s a ton of clinical data and samples flowing through labs across the entire United States, in fact, the world, that are being used for clinical care, but the data and samples are not really being used for research. And so, how can we tap into that?

And that was the founding vision for Ovation. As we’ve evolved, we set up a software-enable platform that works across clinical laboratories to be able to help them with their workflows but also be able to understand what are high-value patients for research flowing through those systems — identifying them, de-identifying their data and samples, and then being able to bring them to the market as multiomics data. What we see, as you know, a really important role in precision medicine is enabling large-scale multiomic data sets. Right now, it doesn’t really exist in diseases outside of oncology and rare diseases. Folks have been building data sets in oncology for almost 20 years, and they’ve seen the benefit of that.

As the landscape gets more competitive with precision medicines and oncology, and there’s still a lot of room to grow there, we see pharma, biotech, and other researchers in academia really starting to turn to — how can they leverage data and these tools to create precision medicines, outside of oncology and rare disease. That’s where we see our critical role.

Chris: What is the relation of data to precision medicine, and how important is it? I know, broadly speaking, people have heard the term precision medicine. I think it’s not always precisely defined, but certainly, in Ovation’s view of the world that the data side of this and the precision medicine side of this are pretty linked. So, I’m curious if you could expand on that a little bit and how you see those two fitting together.

Curt: I mean, if you go all the way back to the beginnings of the industry, people were looking for extracting different chemicals from plants. That has evolved to understanding animal models and how they can represent different human systems. But, obviously, animals are not really a close link. They provide valuable data, and they provide a roadmap to how people react in the clinic. But by no means is it perfect. We’re focused on human genomics and multiomics. It’s the closest you can get to understanding what’s going on at the biological level across an entire human, across their different organs and systems. And having that data from the genomic side, so whole genome through RNA expression of how that is actually expressed in different tissue to the proteins that are produced and ultimately to glycomics and metabolomics, really helps paint a broad picture of the cascade that’s going on at the biological level. And that’s what’s necessary because what people are looking for is what is that target protein or that biomarker that’s going to help people understand what patients will respond to a particular treatment and what patients won’t.

And that way, you can get them on the right treatment at the right time.

Chris: Yeah, that makes a ton of sense. It’s basically like you need this giant cross-sectional database of individual patients and their associated data to really figure out what are the best treatments that we can build going forward.

Curt: Absolutely. And it’s really there to power models for future discovery. So, we’re getting close to the point where there will be enough data in the next five or ten years where you can start to model again all the way from your germline genomics all the way through what’s happening with the proteins at the cellular level. And that’s what’s going to enable a much more precise approach to these targets and biomarkers, much higher success rates in the clinic, and ultimately much higher success for patients, which is the ultimate goal.

Chris: As we continue to accelerate in this world of AI models for everything, a popular one has been applying AI to human health on the protein-folding side. It has been really interesting and very compelling, but it’s less built out in the rest of the healthcare world. Would you say that’s largely due to the data challenge or people not having resources like Ovation before in order to train and iterate on these models?

Curt: Well, it’s both an availability challenge as well as an economic challenge, right? So, let’s start with the economic challenge. To sequence a whole genome of an individual not so long ago was tens of thousands of dollars. We’re now entering the area where it’s hundreds, and soon it’ll be only a couple hundred.

And that’s really exciting because a big part of the challenge was — it was so expensive to create this type of data in the first place. Now that’s being solved. The second part — as people start to allocate budgets to doing that, as the prices come down — are really the availability of high-quality samples that can be de-identified and linked to clinical records.

Because the genomics and the multiomics are really important, but they have to be correlated with highly, highly curated clinical data on the individuals so that way you understand not just what diseases they have and what medications they might be taking but also what’s their journey. Are they getting worse? Are they getting better? Are they having side effects? It’s important to understand all this clinical context to really understand what are the right targets and biomarkers to go after.

Chris: Yeah, so it’s basically, the single point type data is fascinating, but without the deeply annotated clinical record, the data on all of the sort of related conditions around that individual patient and their biomarkers, it’s hard to piece together the insight that you need.

Curt: Absolutely. And scale is another challenge. There are some really good data out there. The UK Biobank has done a great job putting together a tremendous asset. But it’s a really good start. Most of the clients that we’re talking to are talking about millions and millions of patients worth of data.

And so, we’re looking to build upon the success of places like the UK Biobank. And one other thing that’s unique about our model is it’s not something that we’ve collected over 20 years, like other people that have assembled data. We’ve put together our biobank of over 1.6 million samples on over 600,000 patients, about a third of which is tissue, which is really hard to get.

But also importantly, it’s very representative right now of the United States and, hopefully, over time, the rest of the world, where we have a very diverse patient population. One of the challenges with the existing data sets is that it’s greater than 80%, sometimes greater than 90 percent, Caucasians of European descent. It’s hard to find diverse answers when you don’t have a diverse population. And so that’s part of what we’re building.

Chris: I’m curious just as you give people the context on why everything you’ve done at Ovation is so unique. Why has this been hard? I mean, there is data out there, right? Like we know people, like you said, UK biobank is out there. I’m sure that people have heard about 23andMe and some of those approaches, but clearly, it’s harder than that. And so, I’d love to give you a little bit of a window to say, this is a really hard problem that we’ve solved.

Curt: It is a hard problem. And it goes back to what we were talking about earlier in the economic equation versus the scale equation. So when you’re talking about consumer or clinical tests, they have to be affordable. Whether someone’s paying out of their pocket or whether it’s going through their health insurance. And what ends up happening is the amount of information that actually gets sequenced is a small fraction of someone’s actual genome. A very small fraction. It wasn’t until we started to see the whole genome come down to the $100 of dollars that this is starting to become scalable.

What we’ve been able to do on our side is build a platform that not only creates the scale that we talked about, but we continue to add the potential in the next year is hundreds of thousands of samples per month.

And so, what that allows us to do is find through our software and our data, the most interesting patients to study.

And that way we can focus on sequencing those first. When you go into some of the other data sets, part of the challenge is they’re big at the top level. But then when you get into individual diseases, and then you want to segment that population into, mild, moderate, severe, let’s just take the most basic one. And then you add a segmentation on top of that around what drugs they are on.

You start to get to really small numbers. And so having not only an existing biobank that has been scaled but the ability to continue to add new patients, add scale, add diversity, and then capture patients as new drugs are launched in the future is really important to power this type of research.

Chris: That’s a really important point — the Ovation approach there is to continue to build out both the depth and the detail in real time, so you have cohorts that are representative of what’s happening right now with patients and a diverse set of patients.

I think one question that people ask when they hear all this talk about patients is the privacy aspect of it and how you think about that. And I think the corollary to that is, when you talk about larger pharma companies, say, using this data for modeling or approaching. What are they trying to do with it? Is it building amazing new therapies? Is it building great diagnostics? How do those pieces fit together?

Curt: Let me first address the privacy question because that’s obviously of critical importance. We work with common technology in the industry to tokenize, which means we remove all of the patient-specific information, and the software basically translates that into almost a complicated serial number. And the way the software does it, there’s no way to go backward. So once that patient information is removed, it’s completely de-identified. Then, as we add in the clinical information, similarly with the matching token, so we’re not exchanging any information on the patient at all. With that matching token, we then have to construct what the data set will look like and get that certified — so it will not be able to be re-identified in the future. And there are complicated statistics and what data is included and excluded and at what level that goes into that. But we are 100 percent following the same type of processes that I did in my prior life to make sure we ensure the privacy of the folks who are contributing their data. Absolutely.

In terms of what happens on the pharmaceutical company side, at the end of the day, they’re looking to make better medications for as broad a population as possible. But in the precision medicine world, the way that they’re doing that is by identifying biomarkers that help them understand what treatment is going to be right for them at the specific moment in their care journey. And then understanding how they build a portfolio of treatments that help those patients both across diseases as well as along that care journey. The pharmaceutical companies and biotech companies take the privacy piece just as seriously as we do in the rest of the healthcare industry. They understand that having the trust of the patient and having the trust of all of the different stakeholders is of paramount importance.

And so, we work tirelessly with them to ensure that we’re all using and transmitting the data in the right way because that end objective is getting to those precision medicines. You know, I was thinking about “Anchorman” and Ron Burgundy, and I forget what he was talking about, but he said something like, this works 100 percent of the time, 50 percent of the time. And when you think about broad-based medications, they work 100 percent of the time, 30 percent of the time, right? And so, when you’re talking about precision medicines and some of what we’ve seen in oncology, I mean, we’ve seen complete patient populations get very close to 100 percent endpoints in recent trials. And on average, you’re talking about 70 plus response rates, as long as they have the correct biomarker identified. That’s tremendous. It’s not just tremendous for patient health. Which is obviously the first priority. The second is by making it more affordable. Because you’re not spending money on treatments that aren’t going to work.

You don’t have to go through 2, 3, or 4 treatments that aren’t going to work before you find the right one. And that’s the ultimate objective is first on patient health and then on how we can bend the cost curve in the healthcare system at the same time.

Chris: It’s amazing to look at some of the trials of drugs that have failed simply because they gave them to the wrong set of patients. And yet they would have worked incredibly well if they gave them to the right set of patients. And I, And I think that this sort of data approach that Ovation is taking to say, “Hey, go find those right set of patients. There are better therapies that are already out there for you — if we can just figure out what subgroup you are in? Who’s the right set of people to give this to?” And there’s going to be new medicines that will be created using that data that are going to be even better.

Curt: 100%. And so when you look at the first wave of precision medicines that came on, it often was through the route that you said, either the trial failed, and then they did a reanalysis of subpopulations, and then they went and found the biomarkers, and then they redid the trial, or they had enough data to submit the data from the original trial, but with that subpopulation Or sometimes it was even after they were launched on the market, right? The early medicines were launched without biomarkers. And then biomarkers came later as they learned from the market and what their success rates were. We’re enabling people to do that from the beginning on purpose. And that’s the key thing is — why go through that trial and error? And the whole system is learned, right? They’ve learned these lessons tremendously with oncology and rare diseases — that’s why this is a great time for Ovation because as we’re getting this data out to the market, people have already figured out how to do this and now they’re just as they’re changing priorities and moving toward other disease areas, they’re ripe for this type of data to follow the same playbook they did in those other diseases.

Chris: Yeah. It’s incredibly valuable, and I think that it’s endlessly needed by the pharma companies. And that actually brings me to the next great point, which is that on the Ovation side, you’ve really been on a roll for the last year, really landing some of these partnerships with larger companies. I’d love to have you talk about that a little bit — and why now is the time and why it’s been such an exciting time for Ovation.

Curt: I will answer that, but before we, we, we go on, I wanted to go back to the research point. So, our objective, we’ve talked a lot about pharma and biotech, and they’re obviously the most active, and they spend the most money on R and D. But our objective is not just simply to serve those customers. It’s really to make sure that, and we’re exploring, academic partnerships with health systems that do research.

We want to enable research with this type of data broadly and eventually get it in the hands of the payers. Being able to have a set of truth in the data on what’s happening from the research all the way through the market, again, is going to help not only get better medicines and have a better effect for patients’ health. But ultimately, we want to enable folks to make better decisions.

And not just clinically, but on coverage. So, this also starts to bend the cost curve. So our vision isn’t just pharma and biotech. That’s where we need to start, but we want to enable research and decision-making in healthcare broadly with this type of data because that’s the type of change that’s needed.

Chris: I think that’s a great clarification that this data is exceptionally valuable and useful across the entire healthcare and care paradigm. And that whether it’s from the payers or the doctors or the academic researchers who are working on the science, this is the type of thing they need to accelerate their work.

Curt: Yeah, so on the traction front, there has been so much going on. We created our first pilot data set at the very beginning of 2024 and launched it. One of the things that we learned, as you can imagine, is if you were selling just genomics and multiomics data or you were making available just the clinical data, either one of those is completely crazy scientific sales. You have to be in every single detail, not only of what can you do with it, but what is it? Where did it come from? How’s the data model set up? So on and so forth.

A big part of our learning was we needed to show people that we could do this. For a long time, we were a startup with a presentation and a big biobank. And although people got very excited, when you’re asking people to invest in creating these data sets — because even though the cost of sequencing is coming down, it’s still not an inexpensive endeavor.

Chris: Sure.

Curt: So, we created the pilot data set and then were like, how can we get this in the hands of folks so they can see the quality of what we’ve been able to produce? We had to go where the researchers were. And we did that in a couple of different ways. We partnered with DNA Nexus, really the leader in managing and analyzing this type of data across the globe and worked with them both to get to different conferences where researchers in the space — we did irritable bowel disease first, so IBD — where are those people going to learn about what’s the latest and greatest going on in the space.

We put together posters and abstracts, and we got accepted at a couple of the top conferences and were able to present. We actually had small little luncheons as well for people to come and ask questions and give us feedback, and being able to connect where those technical researchers, those technical buyers were — where they normally would show up to learn about new things was really important. And DNA Nexus was a huge part of that.

And then we did pilots. So, we worked with DNA Nexus to get the data into the hands of actual customers and get their feedback. And that was an absolutely tremendous set of learnings for us. And that’s what’s really created the momentum. Showing that we can do it, letting them touch the data, and then being able to say, yeah, we’ve done this in IBD. Now, we can start to do this in other areas.

We just signed our first contract right after Thanksgiving with GLP-1-treated patients. So, both in the diabetes space as well as obesity as, you know, a lot of these patients have multiple comorbidities. So, this is a really interesting group to study. And they’re also having challenges getting reimbursement for these drugs. So, there’s a big push if you could find a response marker, who’s actually going to do well and who’s not. That’s not only going to help the patients, but it’s going to help people understand how to get this to the right people and not spend money when it’s not going to work. Right? Really, really important.

Also, got our first contract in the IBD space at the same time. And we’ve now built a pipeline across, primarily in IBD, but also in metabolic and cardiovascular. I don’t think anyone would accuse those of being precision medicines. So, the opportunity now is we can do a lot, lot better. Especially as we’re learning how different racial and ethnic groups respond to medications differently — male, female. The opportunity to study those from the genetic level all the way forward is right in front of us, and that’s what’s helping us build our pipeline. It’s really exciting.

Chris: Yeah. That is super exciting. And it’s allowing, you know, both obviously Ovation and then your partners to deeply understand what’s going on in all of these areas of health. Obviously, there are the extremely big current ones like GLP-1, but also, to your point, the pervasive ones like IBD and cardiometabolic and places where people have been chipping away at that for a long time and now have an amazing resource that can help them accelerate and move a lot faster.

Curt: Yeah, the other big opportunity that we have in front of us is our collaboration with Illumina which we’re really excited about. We signed that collaboration back in October and have been working tirelessly with them to bring this out to the market and really what excited them about Ovation was not only do we have a large biobank of samples that are already banked and collected. So, we have a lot of inventory where we can work with them and pharma partners to sequence.

And we’re talking about potentially hundreds of thousands of patients’ worth of data through this collaboration, which is really exciting. But the other part is, when we started to show the numbers, because of the mechanism and the platform we have, because we can match the data and understand what diseases folks have before we ever biobank the sample, we have a lot of very high-value patients.

So, if you go out in the normal population and I, customers have told us about other data sets, and I won’t mention who they are. Sometimes, only 20 to 30 percent of the patients are actually interesting because there are a lot of people who got sequenced that don’t have serious diseases that might be healthy.

Chris: We’re both one of those people.

Curt: Yes, well, right now, yes, at least me. But I’m sure there’s something in store for me in the future. And so, being able to get folks that have serious diseases that have multiple comorbidities — and not have to spend the time or the money on the healthy 25-year-old who hasn’t had a chance to get any diseases yet — is really, really important how you put this data together. So that was another thing that was really exciting to them is really high quality, high disease burden set of population.

Third, is really the diversity of the population. So, we have over 190,000 patients and underrepresented minorities. That’s huge in terms of the diversity of the population and then the diversity of the results. The last part is the ability to continue. A lot of the work that has been done is with biobanks that have been collected over 15, 20 years. You go through and sequence it, you create the data, and then you’re done. Either because they don’t have any more samples or the number of samples flowing in is small on a monthly basis.

I mentioned we had over 600,000 patients and 1.6 million samples. That means we have multiple samples on average per patient, and that will continue to grow as we collect more. And so, to look longitudinally at patients, what’s changing, especially when you get into the proteomic side of things, is really interesting because you would expect to see different data and different results over time as their disease progresses or gets better with treatment. And so those are the things that we’re excited about Illumina, and we’re very excited to be and honored to be in a partnership with them and look forward to getting a couple of pharma partners on board to get going.

Chris: Huge congratulations. It’s such a big achievement and such a big partnership that was the result of years of work and reflection of how unique the platform and the data asset is.

Curt: Absolutely, Chris. And I think the good news is we’re just getting warmed up. The team at Evasion has done a tremendous job building the network, building the platform, and bringing the partners in who are contributing data and samples. I’m really excited about some of the academic and health system partnerships because not only will it enable a return of data to them for their own research and put into clinical practice, but also drastically expanding our access to tissue, which is absolutely critical in understanding, what’s going on in the organs at the disease level.

Chris: Yeah. I think the vision, the value already, the acceleration into 2025 —that it’s a good time to be at Ovation, and it’s pretty impressive how this all continues to come together and accelerate. You know, I think one thing we want to spend a little bit of time on is you have an interesting journey to Ovation. You used to run a large business unit at Optum and are a deep expert in the space. I think it would be great just to share both how you thought about that transition from a large, massive company but running a big business unit to now Ovation and also how you think about your leadership philosophy and company building, certainly as you’re building all this momentum.

Curt: Yeah, absolutely. So, for all my former Optum colleagues, it was a big business for everyone outside of Optum, but within Optum it was not by far the biggest business. But it was a really exciting and innovative team and business that I had the pleasure of leading for many years. I really enjoyed my time at Merck another large company, for a big portion of my early career. And then at Optum for the decade before I joined Ovation. One of the benefits is you get to see so many different things.

A lot of what I’m applying here came from my experience at Merck working, watching, and learning from some of the top researchers in the world and understanding how they think about identifying targets, and what does a good clinical candidate look like, and how do we put together the infrastructure to go after biomarkers and bring them into the clinic with the drug candidates. Absolutely tremendous learning experience, and similarly, at Optum, I got to see every single aspect of the healthcare system. Me and my team’s role was how do we bring analytics to solve those problems? And that’s data software and, and people.

Moving to Ovation — a startup — I was really looking forward to it. Optum is very much like a large company that is an affiliation of small companies in certain ways, so it’s not quite the same as a Merck, but still, your flexibility, your ability to pivot, your ability to gain investment and go try new things is, always limited when you’re talking about a large company with know, quarterly earnings and lots of sign-offs and decision makers to get things done. I love the hustle, the ability to move quickly, to try things — not all of them going to work. You try things, you learn from it, you pivot, or you augment what you tried and try something. That part of it’s really exciting, the pace and the flexibility.

Growing up in a couple of those large companies, you are surrounded by people who have had a set of broad experiences and broad relationships and a lot of the same development paths in their careers. In a startup, you’re a much smaller team. And so, by definition, you have people with very different experiences. That is both a positive and a challenge because sometimes you take for granted that person X should understand this or person Y should understand this. But also, on the other end, sometimes you don’t ask the question you should ask because you don’t know that they have that experience. A big part of what I try to do with the team is make sure that we bring the best minds together on any particular problem. But also create a culture of — we’re all going to make mistakes, and we’re all going to fail at certain things. It is absolutely the right thing to do to ask for help. I ask for help from the team at all times. There are a lot of topics that we talked about today where there are much better experts on the team than I, and that’s who I go to when I need to understand something or there is a critical decision. We make sure we get the right folks in the room to make the critical decisions — this isn’t an army of one in any particular area. This is a team. We succeed or fail together. And so, asking for help and asking for people to rally is absolutely the culture that I think we have. And we’re continuing to try to foster.

Chris: Yeah. And I think, you know, to your point, too, it’s a much smaller team, but having those diverse perspectives that are different, right. And sometimes maybe unpredictably different, going after problems that haven’t been solved. And I think that brings me to my last question, which is what is most exciting for you about Ovation and the potential in the coming years?

Curt: I see us as, first and foremost, the world’s leading multiomics data provider with the ability to have very, very dense data for each and every patient. So the way people are doing these things, in general, today, they might have very small data sets with each of the critical components together, but if they have anything scaled, usually they have one component with one population, a second component with a second population, a third component with a third population, and then they’re trying to use analytics and AI to sort it all out. And it’s not to say that that’s not a good approach, given the history of how this field has evolved, because it’s really the only thing you could do.

We have an opportunity to put together all of those different pieces of the multiomics puzzle for the same patient with rich clinical data in a way that can really speed everything up, speed up the model development, speed up candidates into the clinic, and ultimately, to the market. That’s what gets me super, super jazzed. I also think that we’ll have an opportunity, as we continue to grow the data set and add more data, to become true experts in this and start to transition to building some of those models or providing some of the analytics as well. So, our clients can, instead of focusing on how we find the targets and biomarkers, they can start to focus more on model building and application after that.

How do they actually speed things into the clinic? How do they speed things to the market, which is where their true expertise lies. Not to say that they’re not experts in, in finding the targets and biomarkers because they are, but if we can be an essential resource in helping provide those answers, they can then apply their expertise downstream, which we will never have. Right. So that’s, that’s super, super exciting to me.

Chris: What you can do to your point with both the data and the modeling and the analytics on top of it, is pretty incredible. And I think that brings me to the last question, which is you really are an expert in precision medicine. And so broadly, on top of Ovation or outside of Ovation, what most excites you or what’s most going to surprise everybody to the positive in the field of precision medicine over the next five years?

Curt: I think there are multiple aspects to that answer. So, the first is, you know, the benefit to the patient. When I think about 10 years, 20 years from now, what does that look like? It’s actually having multiple biomarkers, so you can actually discern even more granularly what is the best fit because as competition increases in individual diseases or individual disease states — so say mild-to-moderate IBD. People are going to come in; they’re going to copy those individual biomarkers. So, it’s going to start to expand where you start to look at a host of different biomarkers. And I don’t know if it’s three or seven or 10 ultimately where the science goes. But you’re going to be able to discern the patient population even more and more finely.

And what that’s also going to enable is a much more structured way of how you select treatment for the individual, but then how do you actually select treatment across the care journey? So, when the first medication, which is a great fit and is working fantastically, starts to work less effectively in year two. Already have the data and information on that patient as to what, what are the signs to look for, and what’s their next treatment. And being able to have it not just at the population level but across the care journey. I think that’s going to be really, really important.

And the second part of it is, you know, what we mentioned earlier. So, as the population gets continually refined and more personalized, right? And competition increases because there’s more data available, you can go through the development and commercialization process faster, the cost of developing these drugs is going to come down, but competition in the market is going to go up. Ultimately, it’s about getting better care for the patients but also being able to do it at a much more affordable price. Piling on more expensive drugs is not a long-term outcome, but enabling this type of innovation in development and commercialization, and then enabling the coverage and clinical selection with this type of data across the entire industry, is really going to enable people to do this at a more affordable price. And that’s part of the ultimate goal. It’s not just better patient care. That’s number one, but it’s also how can we build this in a way that’s economically sustainable and competitive? So that way we can help drive the cost of health care down for the individual at the same time.

Chris: I think that’s such a compelling vision and to think, if you can really leverage all this data, the ultimate outcome is better care for more patients, much more affordably — such a good vision to have and to build toward. And so Curt, I really appreciate you diving into all of this with us on Founded & Funded. It’s super fun to talk about all things Ovation and precision medicine and all of the incredible acceleration at Ovation. And we really appreciate you having this conversation.

Curt: Thanks for having me. If you ever have an empty spot in your podcast schedule, I can talk for three more hours. So let me know. Thanks again, Chris.

Listen on Spotify, Apple, and Amazon | Watch on YouTube

In this episode of Founded & Funded, Madrona Managing Director Tim Porter and Jama Software CEO Marc Osofsky discuss the intentional strategies that fueled Jama’s transformation from $20M ARR to a $1.2 billion acquisition by Francisco Partners. Marc shares his blueprint for scaling with purpose and embedding efficiency into the DNA of a company. Tim and Marc unpack Marc’s approach to turning conventional wisdom on its head, exploring how focusing on intentional strategies can lead to sustainable success.

Whether you’re looking to refine your go-to-market strategy, enhance operational efficiency, or prepare your company for an exit, this conversation is packed with actionable insights.

This transcript was automatically generated and edited for clarity.

Tim: Let’s start with a quick introduction. I was fortunate to be on the Jama board for almost 10 years after Madrona invested, and you came on several years into that. can you share a bit more about Jama Software? What it does, its journey, and a few of the milestones that led up to this exit to Francisco Partners. And then, we’ll dive into some of the lessons learned along the way.

Marc: Sounds great. Jama Software basically helps innovators succeed. And so we’re focused on companies that build complex products. A product that has software, hardware, electrical, those types of things. So our customers are in the automotive space, semiconductors, aerospace, medical device, and industrial. It’s things with hardware and software. We’re really the first company that’s helped bring those different engineering disciplines together to be able to improve the performance of the product development process. So they can go faster and deliver higher-quality products.

Tim: Marc part of what inspired this podcast was you were gracious and came and spoke to all the CEOs in our portfolio at our recent CEO summit, and that was super well received. And as we were talking, I realized, wow, there are a lot of learnings here that you’ve been thinking about — we should share this even more broadly. And this framework you had for thinking about those lessons learned I also thought was really interesting, and that is to contrast conventional wisdom with this idea of intentional wisdom, so this idea of accelerating growth — so many companies across our portfolio in the world right now has gone through this period of slowdown, and it’s like, how do we reaccelerate growth? How do we keep growing? But how do we do it efficiently?

And the conventional wisdom around accelerating growth is — You have to do it fast. You have to scale your sales team. You’ve got to hire more people, you’ve got to focus on quota and headcount and capacity. But you really focused on something a little different starting from right when you started at Jama Software — tell the group what your intentional wisdom was in this area.

Marc: I’ll share things here that work for us. They might not work for everybody. But hopefully, everybody steps back and thinks a little more critically about conventional wisdom and doesn’t just apply it.

Tim: That is the core point of this notion of intentional wisdom, isn’t it? That you have to find the right strategy for your company and not just think cookie-cutter — what everyone is saying you have to do.

Marc: Right, exactly. This pattern application takes the place of critical thinking. I think the conventional wisdom is you have to hire more salespeople. You’ve got to have more quota capacity, right? It’s very capacity-centric and expectation-centric, right? We can’t hit the number unless we have enough capacity.

The interesting thing that happens if you follow the conventional wisdom approach is you hire new salespeople. They’re less experienced. They generally have a lower win rate because they’re less experienced. They don’t know the market as well. They don’t know the product as well. So you end up lowering your win rates. So you’re increasing headcount, but you’re lowering win rates. So you get a negative capacity effect.

Obviously that’s, that’s one way of looking at it. The way we ended up looking at it was a bit different. So we started thinking about how much demand is in the market? How much TAM is being activated? I mean, this gets into another concept around TAM. There’s a lot of focus on TAM. How big is this market? How big is the potential market? How much is addressable or serviceable? But it’s all about the total potential size of the market. There’s no real focus on how much of that TAM is being activated in a given year. That’s your actual demand — the TAM activation. And so once you realize you might have a huge market potential, but only a small portion of that’s being activated, well, you’ve got to get as much of that as possible.

So what determines how much of that activated TAM you get? It’s your win rate. And so we focused first on win rates. And our win rates were in the 30 percent range when I started. It’s probably pretty typical in a space where you’ve got multiple competitors. We focused on that, and we ended up taking them up to north of 70%, almost 80%. That alone more than doubles your capacity, right? If you think about all the time your salespeople spend on an opportunity and then you lose, all of that time is wasted, right? It’s wasted capacity. So we essentially doubled and even 2.5Xed our capacity just by improving win rates.

So it’s not as simple as just hiring more reps and getting more capacity.

Tim: And just to give folks context — over the period you were at Jama Software, I know you’re a private company, but just to ballpark — $20 million of ARR and 6Xed it in the timeframe. So just, I think that’s also important because sometimes these approaches are either much easier at a big scale or are much easier at a small scale, but you took it through the classic growth range in implementing this approach to growth.

Marc: Yep. No, that’s right.

Tim: I teased the efficiency side of this equation in teeing up growth, and clearly doubling or 2.5Xing your growth rates creates a lot of efficiency. But that is also only part of it, and you got to a very high rule of 40 at Jama, which is growth rate + free cash flow rate. And, if not the conventional wisdom around efficiency, it certainly has been the pattern to grow rapidly — grow at all costs, maybe, and really just grow into efficiency. The thought is — “If we get to enough scale, we’ll get efficient. But if we don’t, then we have to cut.” So you end up in this grow-then-cut trap, which is a phrase you actually used. Talk a little bit about what Jama Software did to avoid this grow-then-cut trap — in addition to this focus on win rates.

Marc: I think it’s, it’s an interesting topic. I mean, maybe some companies have pulled it off. God bless them if they did. I think it’s a really hard thing to do. So, I was always nervous about falling into that trap. And the main reason is I think it’s a completely different culture. An efficiency culture — if you go back to the Walmart days or something and the whole management discipline and culture around Walmart — just how cheap they were about everything they did as a corporation, right? That got embedded into the culture and embedded into how they did business. They don’t want to waste a single dollar and have that increase the prices of the products.

So that culture, I think it’s really hard to flip. Take a company that has a spend-like-crazy culture and then flip it to all of a sudden being efficient, right? Nobody knows how to operate. Everybody thinks it can’t be done. They need more resources. And so I think you have to start that culture early and really demonstrate that yeah, we can grow and we can do these things in a very efficient way and build on that. So we were very intentional about that. It was one of the reasons why we didn’t want to go into the successive spend environment.

Tim: I remember some of the things that you did in this area. Some of it’s a big part of its hiring and team building. So there was very little overhead in the organization. Everyone was either building product or selling product for the most part. Right now, a lot of people are coming back to the office. Frankly, we’re seeing a lot of benefits for innovating and things back in the office, but you went very much remote and found subject matter experts wherever they were. Maybe talk a little bit to some of those actual decisions and approaches you use to bring this culture of efficiency to life.

Marc: We probably are a bit unique in terms of our virtual-first approach. So we shut down the office right after COVID, like most folks. But at that same time, we decided to shift our whole go-to-market team — so sales, pre-sales, consulting, and customer success — to be aligned vertically.

And that we wanted to bring vertical expertise into the company. And when you think about, well, where’s the expertise for automotive versus medical device versus aerospace, they tend to be in very specific geographies in the U.S. and in Europe and in Asia. So there’s, there’s nowhere we could find all of that expertise that could be commuting distance to Portland, Oregon, which was where headquarters was.

For that reason, mainly, we decided to stay virtual first. And we left the office open and available for local folks and they could use it if they want, but we didn’t force people into it. So that was really the main driver. We focused on talent first, not geography or focusing on an office. I mean, there are great things about getting people together, and we still do that. Obviously, there’s huge energy and creativity when that happens. But our primary driver was how do we attract the best talent we can, no matter where they live. And that’s really proven to be effective for us.

Tim: There’s a broader point here that I think was one of really the key strategic decisions Jama Software made, which was to go vertical, to focus on these specific industry verticals that you’ve alluded to a few times. And I think that had an impact on growth, this concept of activated TAM, which maybe you can say a bit more about cause I think that’s really interesting. And a lot of people, including a lot of investors get that wrong, probably. To keep with our approach here, the contrasting and conventional wisdom there is like, you gotta be broad to grow and be big, and that was something that we were trying to do for a number of years at Jama — is be the really broad, horizontal requirements product management platform.

And that just didn’t quite land the way the company started to take off once you put in this vertical orientation.

Marc: I think this horizontal view of the market tends to lead to conventional wisdom for the go-to-market team to be geographically aligned. The original origin of that, I believe, was around assuming face-to-face visits for salespeople and you want to minimize flight time and costs and how many calls could a sales rep make in a day, so you focused on geography and costs. That also leads to treating Europe like a single geography and having a head of sales in Europe, and then that leads to tension always between the U.S. and Europe around accounts because so many accounts are spanning geographies. And that tension never is productive and it’s actually challenging to manage. So that’s the conventional wisdom — do it by geography. So the reason we didn’t, it’s going back to the win rates — as we were digging into the win rates and saying, okay, why are we only winning 30 percent of the time and doing win-loss analysis and really digging into why did we lose and why did we win?

We realized that, fundamentally, we had this horizontal product that was highly configurable. And when we had a knowledgeable person in the sales cycle who knew that industry and knew our product and could bring those two things together in terms of here’s the best way to deploy and configure the product and meet industry standards, we’d win almost all the time.

When we had someone there who just happened to be in that geography and didn’t know their industry and really didn’t know what they were talking about and couldn’t get to the depth of the details, we’d lose. And so that led to say, okay, well, we should really focus on industries and make sure in every one of these meetings that the people leave a conversation with Jama Software saying, wow, these guys really get us, they understand our industry, they understand what we’re trying to achieve.

They speak our language, right? It’s all those things you want to hear. And none of the other companies we talked to do. So that’s, that’s why we focused on industries, and that’s the main reason why the win rates came up.

Tim: I think companies sometimes resist this notion of going vertical because they, I don’t know, overestimate the complete overhaul that it takes to be able to do this. I mean, you did a really authentic job of tailoring product and messaging and customer empathy and understanding into these specific verticals: medical device, automotive, and semiconductor. But I was also impressed that the process didn’t take a decade. You were able to make it happen pretty quickly. And I guess it’s no one thing, right? It’s — you hired people that had the right experience. You put the right playbooks in place from a go-to-market side. You just have to really commit, I guess, across each of those areas, and then you can make this happen.

Marc: Yeah, we tried to be a bit systematic about it. Cause it is a lot when you take it all the way, and now we’ve moved to business units even. So that’s the full extension of a vertical focus. But at the starting point, we focused on the customer and that interaction and the expertise that mattered — start there and start with the demos. And how do we tailor those? And how do we get the right people there from a pre-sales perspective and then post-sales and consulting. So we took each step at a time, and we created templates and approaches that we can apply across all the industries, right? Here’s how we do those things. And we created industry solutions that we productized, right? So, those configurations of the product for each industry become products in themselves. But we didn’t start there. We just started right with the expertise in the moment of truth with the customer at that moment. How do we demonstrate in the product, in the demo, in the person’s expertise that we can solve their problem better than anyone else?

Tim: I’d be remiss not to mention — I think part of what helped you execute here so successfully was there was a great product and a great insight into market need, and the Jamanians that had been there before you had done a great job from the founders to other people. So there was a great foundation, but you were able to tune in ways that really helped growth and efficiency both take off. This concept of culture is come up a number of times. Again, conventional wisdom, right? What is culture? Culture is defined by mission, vision, and values. And those things are super important. Like you need to have those. Jama Software has those. But I think part of your intentional wisdom is that it only really becomes impactful if you turn it into daily habits and behaviors. Maybe talk about how you were able to do that and just your philosophy on how to drive and build a high-performance culture.

Marc: We started with the definition, which I think is always hard. Like what is culture? Most people can’t define it, right? It’s one of those challenging terms. The definition I like the best is, is a very simple one. It’s the sum of what we do and say, which is a very large definition and simple. But I think it helped us focus on very tangible things. We ended up going from that definition of the sum of what we do and say and realizing, well, what drives what we do and say, and it’s largely habits.

And we tend not to think about habits in a work environment. We think about habits in our personal lives, we often think — we want to eat healthy. We want to exercise. Those are habits. But the reality is almost everything we do is habits, and we all have work habits. And I don’t think a lot of us really reflect on those. And so we said, okay, well, what are the habits at work that we want to focus on that we think is going to drive our success? I think one that’s interesting to talk about is our habit to follow the scientific method.

And most people, again, don’t talk about the scientific method when it comes to business. It’s not taught in business schools. But we were really trying to reflect on how decisions are made at companies. What do we do with ideas? How do we prevent the negative things that happen with ideas? People become attached to their ideas. It’s I have my idea. Tim, you have your idea. We’re gonna argue about our ideas. We’re going to get very emotionally attached to them. Which ideas win? It depends more on position or politics — not very rational things. So we said, okay, well, how could we enable more rational decision-making and more transparent decision-making in the company? And how we could get better outcomes from decisions? And so the scientific method is the best method that’s been proven to do that in a structured manner. And so we just modified that for more of a business context.

Then, we used our own software because I wanted to get everyone in the company to use our software. So we’ve used our software to enable the scientific methods. So people go in there and they enter hypotheses and tests and impacts and collaborate with others. And so everybody can see what the potential hypotheses that we might implement are. And they can see the ones that are being tested. So we get the huge benefit of being completely transparent about the thinking that’s going on in the company. So they don’t have to wonder what’s happening.

Tim: I love this. There are three big things, at least, that I took away from what you’re just saying.

One — there’s a mindset shift from ideas to experimentation. And people emotionally holding on to polarizing ideas. But experimentation, that’s a mindset shift.

Two — you actually created a mechanism to do that. It’s not just, Hey, don’t think A, think B. You put in this mechanism.

Three — That mechanism is your own product.

Well, let’s talk about the process — Jama Software has a great land and expand, right? Sometimes, you get adopted for a project and end up being the platform that entire large product organizations at huge enterprises get run off. There are post-sales questions around who owns the renewal? Is customer success just there to drive CSAT, or do they own the renewal?

Almost every company that I’ve worked with juggles how you organize the customer success group, and we juggled it a bit at Jama Software over the years. And it’s also, I think, not uncommon for it to evolve as companies scale and grow, but maybe nuts and bolts here, just explain a little bit how you organize this customer success side of the business.

Marc: The way we went about it. We start with the customer, and we start with the expertise we want to bring to bear. And I think for our situation, we are on the more complex extreme, right? We’re dealing with engineering departments building very complicated products and very advanced industries. And so the expertise someone on our side needs to bring to be able to go toe-to-toe and bring value to a customer is a pretty high bar. That’s really a consultant, I think that’s too high a bar to expect out of a CSM profile. I think, on the other extreme, if you’re more of a horizontal product that’s more workflow or more structured, it doesn’t have this level of complexity, right? Then a CSM can play more of that consulting role.

So I think that led us to put the expertise for best practices and post-sale adoption in the consulting group. And so the CSM team leads all the commercials, leads the relationship with the client, leads expansion conversations and quarterbacking the whole experience, but we’re not putting the extra burden on them to try to, okay. And you have to be an expert in this very complicated engineering field.

Tim: And did that function report to you? You also had a great head of sales on that side — I was trying to remember who actually owned this responsibility. Was it sales, or was this a direct to you as CEO?

Marc: It evolved over time, so now it all rolls up to our CRO, Tom Tseki, who’s wonderful. Previously, while I was in a nurturing state, all of us had so much to do. So I was taking that on. I’m a former consultant, so it’s an area I enjoy.

So, a bit of an evolution.

Tim: Yep. Makes sense. Let’s talk about the process of selling to Francisco. It was an important process and milestone for the company. I think, back to our conventional versus intentional wisdom, there’s conventional wisdom, at least in my world in VC that great exits require sexy market and really rapid growth rates. You had solid growth rates. I mean, your growth rates were 25, 30%. Which are not easy to come by in this market. So your intentional wisdom was a balanced approach with growth and profitability as well as some strategic positioning. Maybe talk about how you really ran that process, including what precipitated it, that it seemed like the right time. And then going all the way through, which was a pretty lengthy set of discussions and strategic decisions that culminated in this majority sale to Francisco Partners.

Marc: It was a bit of a blur then.

Tim: First, it went slow, then it went fast.

Marc: exactly. I mean, the most important thing I think for founders and CEOs is if you can generate the rule of numbers, right, if you can have profitable growth and get that rule of 40 or even rule of 50 if you can get there, as you scale up that lets you really control your destiny more. Because then financial buyers come to the table that really buy on the numbers. And so we were able to attract that whole swath of potential investors because of the numbers and then because of the numbers, then they dig in, some already knew the space, those that didn’t, learned about it.

But that’s the best thing about profitable growth — you bring all these financial buyers to the table. There’s so many of them now, and there’s so many great ones, and there’s so much capital and dry powder out there — and there for high-quality assets that are delivering those high rule-of numbers, the valuations are quite fair and exciting.

The strategics are always more challenging in terms of how they make decisions, how long it takes them to make decisions, what’s really driving their interest in certain areas, and how do you fit into their existing portfolio. So that’s a much different process in terms of your ability to control the outcome and timing.

We had both strategics and financial sponsors involved. And so, we went through all of those different experiences, but I think that’s the fundamental difference, right? It’s, if you did, if you can do profitable growth, and deliver these kinds of numbers and have these kinds of win rates, you can control your own destiny. And then, hopefully, you’re in a fortunate position. You might have a chance to choose between a financial sponsor or a strategic. But only betting on strategics and burning cash and hoping one of them is going to buy you for some really strategic reason, right? That’s a lower probability strategy.

Tim: Yeah. The whole process really was catalyzed by interest from some strategics. I think you and the company did a good job of not thinking about an exit, but just from a business development, a partnership standpoint, who do we need to work with? Who do we need to go to market with? Who does our product work best with? So that kind of catalyzed it. But then, as you said, it turned into, We had a banker — it was more of an auction. Ultimately, I was also struck by the fact that successful M&A comes down to relationships and building trust with who you’re going to go work with afterward.

And even though there was a bunch of interest, and it was private equity, it struck me that that that was really ultimately a big part of how you did that successfully with Francisco. Any thoughts or lessons around, even in these competitive, tense, transactional things, how it’s still really critical to — maybe this sounds like, “Oh, duh,” but it’s hard at the moment to form personal trust-based relationships with who you’re going to work with going forward.

Marc: For those that haven’t been through this, I did more lunches than I think I’ve ever done. Um, and so, yeah, I had the good fortune to meet all sorts of top private equity folks. And I’d say the most experienced ones and the most senior ones do focus very much on that, that personal relationship and spend a significant amount of time with me one on one. It’s all about trust when you get down to it. It’s a very big part of the process. And when I look at the other bidders at the end that came close, it was, again, the strong personal trust that had been built and relationships through the process.

Tim: So, of course, this was a $1.2 billion exit, which is one of the biggest in the SaaS space over the last couple of years. Of course, now it’s like, well, from here, like, what’s the next 3X, 5X, 10X? How is the transition gone? And any thoughts on what this next phase at Jama Software involves? I mean, there’s, there’s always an evolution, but anything to share there on how this transition has gone thus far?

Marc: I think the reason I’m still here and so many of the Jamanians are still here is we’re just at the beginning of this journey. This is not something that we felt we had finished achieving our vision or our mission.

And so we have very good clarity on where we’re trying to get to. And we still have many years ahead to fully achieve that. So I think for all of us, it’s just felt like a continuation of what we’ve been doing. Obviously, we got to scale, and we got to deal with scale. I think the biggest thing we’ve done is moved to this general manager structure, which is a big shift.

And for a company of our size, it’s probably a bit early going to conventional wisdom. I just saw a public company just starting to do this at a much bigger scale. We’re probably early in making this move, but it’s just another doubling down on our belief in the power of being focused on segments and trying to push authority, responsibility, and decision-making down in the organization as much as possible to really be successful and it also creates all these great roles for people.

And that’s been a big part of our success. We’ve promoted from within, we delegate authority and responsibility, we hold people accountable. But so many folks in the company have meaningful roles and having huge impacts and I love seeing that. And frankly, it terrifies me if everything had to flow through me and I had to be an expert in all these industries, and I mean, we’d fail.

Tim: Yeah. And, obviously, we wouldn’t be on this topic if things weren’t going well, but that being said, um, this is super authentic, right? I mean, you and I have talked about it a bunch offline and the fact that things are off to a great start. It’s just not always the case, right? You hear a lot of horror stories about acquisitions, whether it’s strategic or private equity.

And I think it’s just a real testament to how thoughtfully you aligned on a plan and a partnership going forward. And, of course, the foundation that you’d, that you’d built. So, just in wrapping up lots of great thoughts here, I think for companies to think about at different stages of their journey and any last thoughts you give? Most of our investments, of course, are at the early end of this spectrum, right? So, thinking back to when you first took the reins at Jama Software or even before any, any last thoughts or things you’d reinforce for founders and startups out there who are trying to get on the path that you’ve been on?

Marc: Yeah, I think at the early stages it’s really focusing on how much TAM’s being activated. Like, where’s the demand? Really understand where’s the demand? Can you measure it? I mean, you can do a rough measurement of identify all of your competitors or alternatives. How much are they growing each year? How much of that is new versus just growth in their existing accounts, right?

You can, you can get to some estimates. so really trying to understand how much demand there is out there and then really understanding why you win and why you lose, So figuring out, okay, in these situations, if it’s this industry and they have this problem, or it’s this situation, we have a really high win rate, and then these other ones we don’t, right?

So that’s the, just having some discipline there, I think is the, the starting point for everything.

Tim: Well said, Marc. Thanks so much. It’s been fantastic to work together on Jama Software. We would love to find more ways to work together going forward, and all of this advice and sharing these lessons is gold for our listeners and for me as well. So thanks for everything. And thanks for being on Founded & Funded.

Marc: This was great. Hopefully it helps. See you, Tim.

Listen on Spotify, Apple, and Amazon | Watch on YouTube

In this episode of Founded & Funded, Madrona Partner Chris Picardo sits down with Jamie Lazarovits, the co-founder and CEO of Archon Bio. Madrona partnered with Archon truly on day one to spin out from David Baker’s lab in the Institute for Protein Design at the University of Washington. The company leveraged cutting-edge protein design from the IPD to develop a brand new therapeutic modality with the potential to massively transform how we think about treating many categories of disease.

Jamie and Chris dive into how Jamie pivoted from bootstrapping deep tech investments to biotech, how he landed at the Institute for Protein Design working with David Baker — who just won a Nobel Prize, how to navigate translating an academic project into a commercial product with a clear business model, picking a co-founder and building a team, and of course, how he’s building novel types of drugs that will get more treatments to more patients.

This is a great conversation for anyone interested in launching a startup, whether biotech or not.

This transcript was automatically generated and edited for clarity.

Jamie: It’s great to be here. It’s exciting to finally have the opportunity to talk about who we are. We’ve been maybe not that great of a kept secret, but it does feel good to finally share who we are.

Chris: You have told me many times that you started in the startup and tech world by bootstrapping investments into deep tech companies. How the heck did that happen?

Jamie: My best friend when I was in my late teens, he started a software company and he happened to do pretty well. I had some money from my tuition as well as from scholarships and decided to start day trading. This was exciting because we had never played around with something like this before, but we thought, why not do something more mathematical and see if we can figure out trends in the market? At the time, we were playing with penny stocks and the rare earth market, and that was a lot of fun. We did relatively well, but the problem was we realized it was gambling at the end of the day and we weren’t able to see underneath the hood to know if these companies had substance. We also realized we weren’t excited about just making money. We wanted to understand how these people thought about what they were doing.

My friend had this software company based out of Waterloo in Canada, which is a very big engineering school, and we started speaking to a lot of early-stage founders who had amazing ideas but didn’t quite have the right capacity to communicate what they were doing. My friend and I were interested in understanding what was going on under the hood, so we decided to take our tuition money, the money we made from day trading, and the money he made from his company to start investing in these companies. We ended up doing this in about 10 different companies. Some of them have grown to over 100 employees with multiple tens of millions of dollars a year in revenue.

Chris: It’s fun that you got a little taste of our side of the table.

Jamie: Totally.

Chris: Some of those companies are still going. I think that’s super interesting. Not many people have this sort of accidental venture capitalist interlude between graduation and going to get your PhD, but I think it’d be interesting to talk about how you made that transition. You were working with these deep tech companies and then you decided that you’re going to go to grad school.

Jamie: I was working with these deep tech companies. A lot of them were focused on AI. I came from Toronto, so obviously, machine learning is very big over there — they are big in AI and in hardware. It was interesting thinking about how you translate deep tech products to solve real-world problems. I was working at Harvard, and my roommate’s mom invented this device that profiles maternal blood. Instead of a woman having to go for an amniocentesis, you were able to profile her blood, and then you could determine if potentially there was something wrong with her child.

I found this amazing because it opened my eyes to this opportunity of using engineering to solve important problems in healthcare. It inspired me to think about how I could take this deep tech stuff that I had learned and my passion for biotechnology, medicine, and healthcare and integrate that together to find something that is bigger. I ended up finding my PhD supervisor, who’s a world expert in the delivery of materials and nanomaterials, and I did my PhD with him because it felt right.

Chris: I also know that you have a more personal reason for being super excited about the biotech and healthcare side of the world, and I think it would be great to share how that put you on the path more towards biotech and eventually to the IPD.

Jamie: My mom would say that she’d be incredibly upset if I told her that I failed my family by doing a PhD. If I would’ve become a medical doctor, I would’ve been the seventh generation in my family. My father was a physician-scientist, and when I was about seven, he was diagnosed with brain cancer. He was pretty fortunate because he was able to survive two years with that, but if you have a certain type of brain cancer, glioblastoma multiform, it’s pretty much a death sentence. It’s like a 99% mortality rate.

But in line with him dying from brain cancer, at the same time, he was doing absolutely incredibly impactful science. He was an immunologist by trade, worked in organ transplantation, and was one of the first people to develop antibodies. He developed an antibody that is now one of the most successful biologics on the market. It’s called Entyvio. Obviously, he was not here to be able to see that go public, but one of the big things that it taught me was that having an impact is possible. I think sometimes in life you’re taught that these things that you want can’t happen, but when you see something that is tremendously impactful and can help people and improve lives, it does it in a certain perverse way actually show you that it’s possible even though you could’ve maybe believed you could do it beforehand.

Since he wasn’t there, I took a lot of the responsibility of navigating with different agencies because, obviously, it’s a pretty big deal if a medicine gets FDA-approved. It was exciting for me because it was, again, this theme of integration brought me into experiencing what it’s like to see a drug get approved, see what happens when change is real, and integrate that with both my learnings as a student as well with me bootstrapping this deep tech. One of the big things that it came back to is that I wanted to have impact in a way that people wouldn’t have to go through what I went through historically. One of the ways that you can do that is to work with the individual, but if you’re working on engineering or technology solutions, you don’t have to do that. You can have impact beyond it.

Chris: It’s an incredibly powerful story and a constant source of motivation. I think, for me, I just could be lucky that I get to work with founders like you who are so driven to solve those problems. It’s vicariously motivating for me, certainly.

Before we get to the Archon story, which obviously we’re both super excited to talk about, you made it to the Institute for Protein Design, where you met your co-founder. Maybe just give us a little bit of insight into what the IPD is for those of our listeners who don’t spend as much time in the world as you and I do, how you got there, and how you and George met.

Joining the Institute for Protein Design – David Baker

Jamie: The Institute for Protein Design, when I first moved there, felt like the physical, mental, psychological manifestation of the Yukon Gold Rush. It felt that when people were there six years ago, they felt that they were a part of something big, and there was this substance that you could feel in the air that people felt that they were going to have impact or the things that we were working on had the ability to change how we live.

The Institute for Protein Design was spun out of David Baker’s group, and he has this unbelievable superpower of attracting good people, which turns out that’s actually not as easy as it sounds. And because of the magnetism of the excitement of the technology, but also people to be enabled to pursue science creatively, it’s built this institute where people pursue design, computational protein design to solve problems, but without predisposition of what those problems are. So people can come into the institute with complete and open creativity, and that’s encouraged. What’s cool and interesting about it is that it’s very rare to be able to go somewhere where you are completely supported and financed to be creative and imaginative and be given everything that you need to do in order to get things done.

Chris: And maybe do some awesome protein design along the way. We’re talking about David Baker who is the founder of the Institute for Protein Design and invented the modern version of the field. You and your co-founder, George, were part of that along the way. Do you want to talk about how you and George met, it’s a serendipitous story, and why you got working on the Archon technology?

Meeting Co-Founder George Ueda and the Birth of Archon

Jamie: The interesting thing about life is that there’s only so much that you can plan, and the big part is being open to opportunities when they present themselves. In this case, this was like anything but an opportunity. There was a going away party for someone who had been working at the IPD, and this was about five and a bit years ago. I happened to sit next to George Ueda at a dinner table, and we were both drinking a beer, and he had made some comments about being half Japanese, and I’m like, “Oh, I just came back from Japan.” We started talking about our passions and the things that we were interested in, and it had nothing to do with any professional overlap, but we got along well and decided to, I don’t know, chat the next day at the institute. What we realized is that he was working on some pretty cool technology. He architected the technology with members at the IPD, and the problems that he was speaking about were very familiar to the types of problems that I saw in my PhD. He was such an interesting person and easy guy to chat to, I just started to pursue it and pause it, is there cool opportunity to maybe do something together here?

Chris: I think it’s interesting that there wasn’t pre-planning involved. You didn’t go to the IPD with the idea of, “Hey, I’m going to start a company.” You didn’t go search out a co-founder of the IPD with the baked-in idea, “Yeah, we have to find a company to start just to spin this thing out.” You guys met at dinner and started working on really cool technology.

Jamie: Part of that is true. The other part that is not is that when I did leave my PhD, it was a difficult process for me to figure out what I wanted to do with my life. My friend Carl, who’s a co-founder of the local company Neoleukin, told me that I need to come here, and that protein design is the most amazing thing that I need to be aware of, and this was seven years ago.

When I spoke with David Baker and Lance Stewart, who is the chief strategic and operations officer at the IPD, I told him that I had a strong desire to be able to build a technology that had impact. The amazing part of being able to use computation was that you could explore space in ways that you could not have done with other types of technologies. I did come to the IPD with a feeling and a notion that I wanted to have impact and translate, but it wasn’t at the expense of doing something that had quality. So I guess like 50/50 there.

Chris: I remember visiting you guys in that tiny office where you sat six inches apart from each other, and it was boiling hot, and being like, “How do they get any work done?”

Jamie: When you do that for four years, you get pretty used to it.

Chris: I know we’ve talked about your background a lot, and I think that’s important, but now we get to the exciting part, which is that for the first time, you were going to talk about Archon publicly. We’ve announced the company, and the fundraising. I think there’s a huge amount of tailwinds behind what you’re doing. What’s the revolutionary technology? I’m going to give you the space to describe out loud what you’re up to and why we’re so excited about it. But we have to talk about the fact that David Baker just won the Nobel Prize, which I think is a phenomenal achievement and honor for David and the IPD, Seattle, and everybody that has worked with him along the journey to get there, which is not over. Start with the work that George and David, George being your co-founder, were doing at the IPD for the 11 years that George was there before Archon.

Jamie: The most interesting thing about protein design is that it wasn’t designed with the intention of application. It was more from this mathematical, almost artistic pursuit of, can we do this? Can we make structures that have never existed in nature before? Can we represent beautiful shapes out of amino acids that give rise to proteins? The interesting thing is, back in the day, even being able to put little pieces, little Lego blocks, of proteins together was incredibly difficult to do. Where the field was about seven, eight, nine years ago was that. Then as complexity began to increase, it was like, okay, well, can we add on to the complexity of the types of structures that we can make?

Then it took a lot of insight from people like my co-founder, George Ueda, and other really spectacular members of the IPD to start asking the question, okay, well, if we can make these shapes, is there a chance that these shapes can do something? There was this fascinating transition where George invented vaccines that are in the clinic right now. He was one of the first people to be able to show that you can use a design protein to tune the way a cell behaves and communicates. Now we’re at this completely whole other side of the coin where we now have this public affirmation and confirmation that protein design is big, it’s impactful from a scientific and technical standpoint, but now the next step is, okay, what can we as a community do with it? What are the real problems that we can solve? And that’s where companies like Archon fit in.

Chris: I think that’s a perfect transition. On the theme of design proteins that can do something, maybe give a description of what Archon is. What are AbCs — Antibody cages? What’s the underlying innovative technology that you guys have built?

Revolutionary Protein Design at Archon: Antibody Cages (AbCs)

Jamie: Archon is a biotechnology company that has created a new class of protein-based biologic to solve significant problems in the medical space that other technologies cannot. Antibody cages, or AbCs, are at this intersection of generative protein design and molecular engineering. They help resolve a long-standing problem in science with this unique engineering solution. This long-standing problem in science is how do you make a drug that gets to where it needs to go, doesn’t go to where it shouldn’t when it’s where it needs to be, it stays there, and it does its activity properly. It turns out that’s an incredibly difficult problem to solve.

Chris: You’ve reduced drug development into the simplified form, but that’s the game, right?

Jamie: Exactly. If you study over decades and decades and decades in the pharmaceutical industry, what we’ve learned is that it’s the shape, size, diameter, and the flexibility of a drug influences the way it travels inside of the body.

Chris: It’s super interesting. You can, by changing the shape of the AbC, change the efficacy profile, the delivery profile, and you can get these antibodies to where we want them to go and engage with the target totally differently. And then what? What effect does that have the ability to do that on the underlying disease or pathway that you’re trying to modulate?

Jamie: Fundamentally, it comes down to what we call the therapeutic window. It’s a balance of on-target versus off-target effects.

Chris: What does that mean?

Jamie: If you look at people that have taken chemo and they lose their hair, that’s a consequence of how the drug works. The reality is that the drug is distributed to many, many different places. You have this balance of how much drug can be added that gets the profile necessary and how little possible you can use in order to not have all of these super negative effects. By changing the geometry and these unique properties of our structures, we have this finer ability to tune either going up into our desired site or away from those sensitive sites that are going to cause some of those worse side effects. It’s this bio-distribution-enabled what we say is a modulation of therapeutic window, which is a huge opportunity in a variety of different therapeutic areas that either get too much or too little efficacy because if you have too much of something, you can get a lot of toxicity, and too little of something, you’re the safest drug in phase one.

Chris: To clarify for everyone, because I’ve been able to see all the visuals and it helps. What you’re really talking about here is the underlying cage that you’ve built out of proteins, which can take any number of shapes. It could be a pyramid. It could be a cube. It could be an icosahedron, a classic geometric structure that you’re able to link antibodies into naturally, so therefore, they’re fixed in a geometric position.

Jamie: Exactly. Yeah, thanks for bringing that up. The antibody cage system is you have your antibody of interest, you have your design protein of interest, and you mix them together and they spontaneously form this rather beautiful geometrically defined structure. It’s the geometry of this structure that dictates how it travels in the body, how it interacts with its tissue, and how it elicits its behavior. It turns out that making that is very difficult, if not impossible, without the advent of these computational protein design methods.

Chris: And now you can make a lot of them.

Jamie: We can make a lot of them. The core innovation that we’ve done is not only on the backend AI, but it’s also on the manufacturing. Sometimes, when you make a technological solution, sometimes you overthink how it can be integrated. One of the core things that we tried to do when we were making this technology was figure out how this can be as easily insertable into downstream manufacturing of antibodies as possible. Antibodies are the largest class of therapeutic in the biologics market, and often, when you change an antibody, you lose all the features that made it great in the first place. As we try to ask a pretty simple question, how do we not do that? That’s where our unique manufacturing has come in — because we now can do that. We can make any number of these, but fundamentally, it’s using AI to solve a very defined problem that not only allows us to tune biology but also allows us to tune biology without compromising manufacturing and production of the therapeutic in the first place.

Chris: We’ll get into this tuning topic because I think it’s particularly interesting, and it’s a theme that has started to come up with a lot of AI plus biotech companies, but one of the ways that I think about Archon is essentially unleashing the full power of antibodies. Antibodies transform that’s the tagline. Can you give a couple of non-technical examples of why this cage structure with antibodies just elicits a totally different type of behavior or what you can achieve that you can’t with an antibody alone?

Jamie: I can give an ultra-colloquial example.

Chris: Sure.

Jamie: If I yell at you and tell you to do something, you’re probably not going to be that enticed to do it, but if I ask you nicely, you’ll maybe be more interested. So it’s the structure and the composition of how I ask you to do something that really matters, even if it’s the same words. What we found on the cellular level is that it’s structural. It’s explicitly how you ask the question and how you interact and engage with the cell that determines its proclivity to actually do something for you.

Chris: So you’re saying, hey, if you have one antibody that’s the drug and it goes to a target of interest on its own, it may be safe, but it might not have any effect.

Jamie: Exactly.

Chris: If you stick it in your cage and you bring several antibodies in a very geometrically specific confirmation to that target of interest, you might be able to elicit a massively different effect even from the same underlying antibody.

Jamie: Exactly. The most interesting thing is because we can control the structure, we have the ability to tune across the entire plane of behavior. If you want something that’s super strong, if you want something that’s super weak, if you want something that’s in the middle, you have the ability to do that. That’s because of the power of this geometric control and tunability that I’m talking about.

Chris: This is one of the things I get so excited about, and you and I have talked about forever, but if you think about the old paradigm of, if you want to try to figure out the range of what antibodies are going to do, you have to maybe mutate them one by one, do this in parallel, and it takes a long time and you might not get great data. You might not even get any of the results that you want. What Archon has said is, “Hey, just take those same antibodies and let’s try the entire spectrum of geometry, and we can show that just based on the shape, we can get very different types of behavior out of it.” I think that’s an incredible fundamental approach to how you’re thinking about building products.

Jamie: Totally. We like to say that we’re trying to turn drug discovery into an engineering problem in the sense that if you decrease the probability of failure of even being able to generate one of these structures, you can ask the pretty basic science or clinical questions, how do these pathways work? What did failure and success look like in the clinic? Is there a way that you can generate a molecule to be able to hit specific metrics you want to get? It totally redefines this whole notion of a TPP because, classically, our target product profile, excuse me. So often, what happens is you have a molecule, and it has its behavior, and the question is, how much can you modify it in order to get a desirable profile that you want?

Chris: Every time you modify it, something else probably goes wrong or at least changes in a way you didn’t expect.

Jamie: Exactly. From our case, we take it from a slightly different perspective. We’re not going to be talking about our programs today, but for our lead programs, we’re starting with very well-characterized and understood biological pathways where we’ve seen how these types of molecules behave in the clinic. By starting from the first principles of how this biology transforms or translates into a clinical setting, we can recursively go backward and ask, how do we change the structure in order to move towards or away from that specific behavior?

Chris: Ultimately what you were creating are drugs that are fully owned and developed by Archon to treat diseases or to go after targets that were otherwise not other modalities weren’t able to hit.

Jamie: Exactly. The nice thing here is that antibodies are increasingly commoditized. From our standpoint, what is unique is that we own this design and manufacturing process to generate the AbCs. It gives us the opportunity to choose which program areas we want to own, which ones we want to go into, and which ones we are going to be open to potentially co-develop if that’s of interest.

Chris: Ultimately, we will have a pipeline of our own internal drug candidates that are Archon and maybe a couple of things that we decide there are really natural partnerships out there with larger pharma or people with great disease insight or biology insight that we can work with.

Jamie: Exactly. We have an internal pipeline right now just not talking about it today.

Chris: I think this is a great way to talk about where AI plays into the story. I mean, at the IPD, you guys have built pretty much all of the fundamental generative protein design tools that are out there. Certainly, the IPD and DeepMind are the leaders in the space. So you have your hands on everything or both hands on them and have built them yourselves while you were there. And so, how does AI fit into the story?

The Role of AI in Protein Design

Jamie: AI fits into the story because it is the crux of how we solve the problems that we do, but AI also isn’t the be-all and end-all. I think that there’s this misnomer in, let’s say, more of the information sciences space that we can throw these models at biology problems, and they’re going to be inherently useful. The thing is, it’s a highly multivariate, multifactorial space that you don’t even know the implications of what you’re doing has on an even more complex and chaotic system like the human body.

We’ve been incredibly fortunate to be surrounded by the best and brightest minds in the protein design space, but not even protein design. It’s also all these people from all these different unique backgrounds that aggregate at the IPD. The big thing that George and I were focused on was how do you change and control structure? How do you change and control distribution? How do you do that by not compromising these desirable manufacturing features that we like in the first place? AI has massive power. It’s hugely enabling, but it has to be constrained at first in order to know how to use it and for what problems.

Chris: I think one of the concepts that you and I talk about a lot is the product-led platform. AI is deeply embedded into everything you do, and it’s not the product of Archon. For the non-biotech part of our audience, we’ve talked about this a lot. There’s a lot of AI and software and compute sophistication going on under the hood here.

Jamie: We’ve been very fortunate, again, to come from the IPD. In particular, I think what really differentiates us is this extreme focus on these particular problems, especially in these target classes that have this well-characterized biology, but again, we view that we’re leveraging these models in a wholly unique and differentiated way.

Chris: I know that everybody can now check out the new fancy website that’s up and live if you want to see some good examples and animations of what this looks like in practice. Switching gears a little bit, I think for the rest of our conversation, we can talk a little bit about the company-building side of this. As we hit on before, these companies, they don’t come from nowhere, right? There is a lot of building and process that goes into it. You and I knew each other for two years before we started the company. Effectively, you started the company, and we provided the capital to help you do it, but we spent a lot of time talking about this beforehand. I think to start, how do you think about translating the academia and what work you and George were doing at the IPD to the commercial world, and what have been the major learnings and insights that you’ve had now on this journey for two years post-IPD?

Jamie: The first thing that I learned when I was doing my deep tech investing bootstrapping days was the importance of framing a problem, and understanding the problem that you’re solving, and knowing when to ask for help. I think the third part is really big is, which is academia. David, at the IPD, will talk about this communal brain and everybody benefits from this communal brain, but fundamentally, in the academic setting, it’s very individualistic. You are almost devalued from working with many people because your currency is your first authorship. And so it’s very difficult to know how and when to ask for help if the system itself is almost pressured to de-incentivize that.

So one of the biggest parts is that there is this ego associated with being exceptional, being able to build things yourself. When you’re trying to translate a really sophisticated technology, it’s just not possible. You cannot develop it yourself. One of the first things that you have to switch is you need enough of an ego to think you can do something that nobody else has done, but not so much of an ego that you don’t know how to ask for help. You have to find people that can really benefit you and transform your perspective in a way to solve problems that you may not have had the predisposition of solving before that.

Chris: What’s a good example of asking for help? I know for the people who are still in academia or still thinking about starting a company or making this transition, do you have an example from “your own process here where asking for help might’ve been hard but was totally the right thing to do?

Jamie: Probably the biggest thing is that I spoke to George and I said, George, I’m not the best protein designer, but you’re really freaking good. I’m able to conceptualize and focus the problems in completely different ways based on my technical background.” Instead of me trying to confine him, what I actually did was try and find a way to enable him and enable myself where we could solve different types of problems together that actually allowed us to do better faster. A big thing for me was that I had been working in design for a while, but finding someone who was able to complement me in a way that really enabled me to be better, allowed me or forced me to look at what was I good at, what is he good at, and is there a way that we can benefit each other?

Chris: That’s a very powerful message about putting together complementary founding teams and playing off your co-founder really well. The other thing you guys did that was unique was you weren’t ready to start the company for a while. Like I said, we met each other two years before I think you technically really started the company. I think I swung by that small office a lot, and we’d have a chat in an update, and I’d be like, “Hey, are you guys ready yet?” You’d be like, “No, not yet.” And then finally you were. So what gave you the confidence to say, “Hey, we are ready. We made that go-no-go decision, and now it’s time”?

Jamie: We viewed that decision matrix and this lens that they, maybe some engineers will take offense to this, but it’s fine. I’m an engineer. There are science problems, and there are engineering problems. A science problem is something that we view as having a nonlinear relationship between input and output. You can put tons of effort in, but you don’t know if you’re going to be able to solve it, or if you are, you don’t know how long it’s going to take. We view engineering problems as those that you’ve confined and constrained the space and how much effort it requires. It’s a matter of the input.

In our case, we didn’t want to be entrepreneurs and build out this technology for the sake of it. We understood what we needed to overcome, we understood the problems that we needed to solve, and for ourselves, there is this integrity piece where we said, “If we can show to ourselves that we can resolve and implement these unique features of the technology to solve these types of problems, that we would have the conviction to stand behind it.” We were given a really hard time during the COVID bull markets. We’re like, “You’re crazy. You’re working in protein design. How could it ever get hotter than it is now?” Turns out it got a lot hotter.

Chris: It’s gotten a little hotter.

Jamie: It got a lot hotter. What we did is we really followed the data. By doing that, we felt that we really presented ourselves as people that could be trusted. Then, obviously, the story had to follow suit with that. Once we really hit those key data points, that was when we were like, “All right, we’re ready to go.” What we didn’t realize is how quickly it was all going to come together.

Chris: We did move from our regular check-ins to, hey, there’s a company now pretty dang quickly.

Jamie: It was really quick.

Chris: That was a fun time over the holidays and going into the new year of a lot of work, but I’m glad we did it.

Jamie: It’s an exciting process when you get investors that want to put money behind your idea because sometimes it feels like you’re playing the sandbox until people are willing to put real money forward. There’s this massive aspect of flattery where it’s like, wow, okay, finally someone or somebody is interested in what I’m doing, but there’s this other side to it where, again, going back to this whole relationship piece, is that the quality of your investors, the quality of the people that you have around you are going to be the critical determinant in you being able to execute on this. If you think anything is hard in academia, multiply that by however many fold you want once money is on the table, once the stakes are a lot higher, once you can’t just happen to write another grant to keep people working in your company.

The big thing is when you’re looking for an investor and why we’re happy with you Madrona is that when somebody tells you who they are, you should trust it. You were incredibly honest with who you were as people, what you were going to do for us. In fact, you’ve done more for us than I would’ve expected. I think that’s what you want to look for when you’re looking at an investor is that it’s not whether or not they’re high profile, but whether or not you legitimately trust that they’re going to support you and be honest enough with you to overcome problems when they will inevitably be in your face.

Chris: I really appreciate that, and so does everybody at Madrona. I mean, one of the things we focus on the most is just helping our portfolio companies and founders as much as we can. And B, I think it’s an important lesson for lots of other founders. I mean, the fit is important between you and your visions and what you want to do and the alignment with the investor base and capital, and not everybody fits with everybody else.

As you’ve been in the CEO seat now for a while, you’ve developed and probably already had, but you certainly have stronger views on team building, how you’ve chosen to recruit, who you’re hiring, and really what you look for. It’s a little bit different in how you frame it than maybe lots of other companies. I’d love you to talk for a second about what’s your thesis on talent and how do you think about adding people to the team and specifically to your culture.

Jamie: If you acknowledge the importance of yourself individually, that’s very important because we need accountability, but the other part of it is knowing that in order to be your best self, you need great people around you. Matt McIlwain said a pithy thing, which he’s very good at, is you want to find people that are cross-functionally useful and cross-functionally curious. What I found really interesting is when you build teams and everybody talks about what their corporate values are, what they look for in individuals, it’s interesting because sometimes one can say something and believe it, and other times you can say something and not believe it.

For example, you could tell me that you want to wear multiple hats, you can tell me that you’re curious, but are you actually? That’s something that we have heavily prioritized for our people that value relationships that can take a longer term perspective, we look for people that want to have impact. That sounds insanely cliche, but the reality is that if you’re an intuitive and emotionally intelligent person and you start actually having conversations with people, the biggest thing that you can hear is what they get excited by. For us, we are constantly looking for people who are good people, they’re great at what they do, and they’re curious and excited about learning multiple things and doing multiple things.

Chris: The bar is quite high to get a job at Archon, which is great. Every company talks a lot about raising the bar on who they recruit, but it’s an extra high bar on cultural fit and how you guys spend a lot of time thinking about the culture of this team and what that means when we add new people to it. Are there certain types of people that you’ve found you really are out there looking for, or hey, these are really great when they join the Archon team?

Jamie: Honestly, it’s been just completely organic. It goes back to this point of treating people how you want to be treated yourself. What we’ve found is that enabling, supporting, and advocating for people on our team, that’s, unfortunately,, a little bit more of a rarity, and we would like to believe it. Then the other side of it is that if you’re incredibly supported and you’re working on amazing technology, then all of a sudden it becomes a highly desirable place to work.

What we found is that all of our intake has been completely organic. You have people that hear what it’s like to work with us and that we’re people that back up what we say with action. It’s been nice because everybody that’s come forward has been through an organic connection with someone on our team. The really interesting thing is that we have teammates that are telling people how much they like to work with us, and then you have other people coming up and asking, “Is there even an opening?” These are for job positions that we don’t even have. They don’t even exist yet.

Chris: This is why you’re the worst, best-kept secret in protein design.

Jamie: Yeah.

Chris: We’re getting to the end of our conversation. I know you and I could talk about this for hours and could’ve probably spent a lot of time just in the technical depths of why the technology’s so cool. I’m also curious about what you are most excited about going forward, both for Archon and just in general.

Jamie: There is something really gratifying about being able to let people know who we are, what we’re going to do, and we’ve been living this. Obviously, now we are public, or not public, but we’re not in stealth anymore. And it’s really nice to be able to share what we’re doing and also speak to people that are just ultra technical in the know and they look at what we’re doing and they’re like, “Wow, I’ve actually always wanted to solve this type of problem, but I’ve actually never known how to do it. If this works the way you guys are trying to build this, I mean, this could be the new gold standard.” That’s a huge one I’m excited for because, thematically, we want to be able to back up what we say with action, and being able to leverage the financial support that Madrona and our other investors have been able to offer us allows us to make this a reality.

Chris:

I know that everyone at Madrona has been just thrilled to be a part of the journey and to help you guys get to where you are and for the rest of the journey to come. I’m just also honored that we were the ones to be able to talk about this together in person for the first time. I really appreciate you having this conversation.

Jamie: Thanks a lot, Chris.

Listen on Spotify, Apple, Amazon, and Podcast Addict | Watch on YouTube.

In this episode of Founded & Funded, Madrona Managing Director Tim Porter and Venture Partner Patrick Ennis host Chris Diorio, co-founder and CEO of Impinj, the pioneer and world leader in RFID technology. Patrick and Chris have known each other for more than 24 years, since Madrona and ARCH Venture Partners co-led Impinj’s first round of financing in the summer of 2000.

In this episode, these three reminisce about old times and share some fun stories while diving into what it takes to truly launch a new category — and the patience required by both entrepreneurs and investors when doing so. They also discuss developing new speculative technology, navigating channel partner relationships, making it through an IPO during uncertain times, and how Impinj became the least known $4.6 billion public company in Seattle. This is a must-listen for any entrepreneurs out there.

This transcript was automatically generated and edited for clarity.

Patrick: Impinj is a massive success story, but many people may not know about it. Why don’t you just tell us? What does Impinj do?

Chris: We make miniature radio chips smaller than a grain of sand. Really smaller than a grain of sand. We were joking that our radio chips are about equivalent in length to 50 bacteria. With those radio chips, enterprises can track their items, get inventory in stores, know that all the items in a medical crash cart in an emergency room are in the crash cart, and there’s a myriad other uses.

Tim: Impinj is such a special place in Madrona history and for me personally, so this is particularly fun and gratifying. When I started in Madrona in 2006, Impinj was one of the first companies I got to work on with our co-founder, Tom Alberg, and our colleague Suja Vaidyanathan at the time. Patrick was working at ARCH but was in the same office with Madrona. I literally met him on my first day in 2006.

And so, now here we are, and what a huge success story and never a straight line to success, which we’ll get into, but let’s go back to the beginning and the founding and the original deal.

$15 million round in 2000. Everything that was getting funded then were dot-coms. And here’s Chris, a new-ish star professor at UWCSC from Caltech, partnered up with one of the industry’s fathers, Carver Mead. I’d love to hear, Chris, a little bit of the founding vision around disposable semiconductors and RFID. Were those things even thought about then?

Patrick, maybe you can comment on a $15 million round in 2000, which was big. How did ARCH and Madrona come together in the founding of the company in the beginning?

Impinj’s Pivot to RFID

Chris: The founding vision was none of those things. The founding vision was a wireless technology that allowed us to make very, very low-power radios.

The original idea behind the company was we were going to use that wireless technology to improve the power efficiency of base station radios for the new big thing, 3G wireless.

Then the dot-com bubble burst, the bottom dropped out of that market, and we had to find something else to do. And so, we looked around. We did a lot of analysis. We looked at ultrasound and GPS and many things. We settled on RFID because, with our wireless technology, we could make, like I said, miniature radio chips that were tiny. I mean so tiny that with the naked eye you can barely see them.

Those radio chips absorb their operating energy from radio waves, so there’s no battery. We said, “We can make these chips. We can put an identifier in them. We can allow enterprises to get information about their items and then, going forward, ultimately enable people to get information about their items.” We started going down that vision.

Then nine months later, Walmart made an announcement that they were going to track all pallets and cases using this RFID technology. We all high-fived. Woo-hoo. Success. We’re going to IPO in 18 months. We’re done. Well, as we’ll get into, we weren’t done.

About 14 years later, we IPOed with a lot of ups and downs along the way. As I look back now, I can truly say any transformative technology takes time. A long time. It doesn’t happen overnight. That was a learning experience for me.

To go back to the beginning, the plan we initially had didn’t materialize, so we focused on a new one and made it work.

Tim: As is so often the case, and thus the Internet of Things was born. Patrick, how did ARCH and Madrona come together to want to do this deal in that size round and convince Chris? Maybe comment on Carver, too, and his role in those early days.

Patrick: Well, it’s interesting you say that because we’ve looked through the files, and there’s no mention of RFID for the first two years.

Chris: That’s correct.

Product-Market-Fit Wilderness

Patrick: That’s not an exaggeration. There’s everything from medical ultrasound to cable modems and DSL and 3G. We were wandering around the product market fit wilderness for a while, and that can be frightening, and you’re told not to do that. But sometimes it’s a good thing when you have a breakthrough technology. If you pick that application too early, you may not ultimately realize all the value. Now, that’s bad advice in general to entrepreneurs, “Don’t worry about your application,” but sometimes, as long as you keep the burn rate low and you’re smart about what you’re doing, then it’s the right move.

Speaking of the round, as you point out, in the year 2000, if you discount back inflation, that size round, seven and a half million from Madrona, seven and a half million from ARCH, that was a fortune.

Chris: Thank you, Patrick.

Patrick: It took a village, but I think in part because we sincerely thought that might be the only round we did. Chris, you had great interest from all the top firms in Silicon Valley, partly because of what you had achieved in your relatively young career, but also due to Carver Mead, who is as consequential a figure as there is in the history of technology in the last 100 years, and that’s not too much of an exaggeration.

How did you view that working with Madrona and ARCH and our founder, Tom Alberg, and working with us versus going with some of the Sand Hill Road firms?

Chris: There’s a lot in those questions. Well, first on the $15 million, at the time we founded the company, I was a three-year faculty member at the UW. They did have $15 million, which was kind of off-scale for me. It’s truly amazing that we were able to raise that amount of money. We thought it would last forever, but of course that amount of money never lasts forever because you’ve got a ton of work to do, hiring people and all the things along the way.

We ended up doing multiple subsequent rounds and, I believe, raised something in the range of about $125 million over the course of the company before we IPOed. But again, we were truly developing a transformative technology.

Going back to those days, we had Tom Alberg on our board. We had Patrick on our board. We had Carver Mead, and it was the collective experience of you guys that settled the company and allowed us time to really think and pursue opportunities. Anytime a major problem came along, and I was all frustrated and all worried, especially Carver and Tom, they’d say, “Relax. It’s okay. Why don’t you look at it this way?” It was that kind of wisdom and it’s more than wisdom. It was that experience and their ability to drive confidence in the paths we were taking. Confidence even though we didn’t at that time know which direction we were headed or how we would get there. It was that confidence that really helped build the company.

And so, you go out, hire good people, hire the best people you can, hire only people that are better than you are, and I truly mean that. With a strong team, you will in general find a way to be successful. We have a set of principles that underlie the company, and they are the most important things to the company. When I go to customer meetings, I’ll often start with our principles. They begin with, “Be respectful. Always act with integrity. Always think big. Always trust your instincts. Always be curious and listen,” and they end with a saying by Patton, which is, “Tell people where to go, not how to get there, and you’ll be amazed by the results.” Those are our principles.

Then we have our mission statement, which is separate from that. Our mission in the world is to connect everything, and we’re going to do it.

Tim: It’s so instructive, and you can have breakthrough technology and world-class technologists, but company success comes back to culture and people. That cuts across all of the great companies that we see here at Madrona.

Founders get to that culture in different ways, though. That’s an amazing set of principles, and you’ve articulated it well, and the company lives them every day.

Did those kind of happen organically? Did you and Carver specifically say, “We’re going to write this down early,”? How did you kind of create that originally and then cultivate it all these years?

Principles and Impinj Company Culture

Chris: It didn’t happen early. It happened later on in the company’s history. We had a set of ways that we behaved, but they weren’t codified in a set of principles. It wasn’t even until after our IPO.

Tim: What year was that?

Chris: We IPO’d in 2016. The principles came about, I think, 2017 or maybe 2018 where we sat down and said, “Okay, the company’s growing. We’re getting more and more people. It’s time to write these things down.” They were not new. They were a set of sayings and actions and the way we behaved. They weren’t new, but putting them down on paper was an important step in the growth of the company. We were living those principles up to that time.

Today, I believe my number one job as CEO is to give every employee at Impinj the opportunity to be wildly successful because, if every employee is wildly successful, the company can’t help but be wildly successful.

I believe every employee’s job, and I tell them this, is to do everything they can to make our customers wildly successful because, if our customers are wildly successful, we can’t help but be wildly successful. That is the vision of the company and how we behave and act. The principles kind of codify that, but it’s our viewpoint and how we go to market, how we act as people in the company, and it is the most important thing to our company, bar none.

Tim: Geniuses taking complicated things and making it simple. That’s a great example, but it’s hard to put it in practice, and you all have done a great job. Let’s go back to the story. We talked about the founding, and you mentioned Walmart making this big announcement but then sort of teased maybe that didn’t play out exactly like everyone thought.

Chris: It did not.

Tim: You mentioned it was 16 years to the IPO. Many fits and starts. We sort of joked RFID, once defined as a market, was still the market that was one or two years away for 10 years, or 15 years.

How did the company persevere, continue to execute and grow, despite a market that arguably took longer to develop than maybe you thought when you first defined it and honed in on it?

Chris: There’s two answers to that question. I think part of the answer is, if you have a vision, and you truly believe in it, and you can see it, you know it’s going to be there. You can just see it. Don’t give up. Just do not give up. Persevere and say, “I’m going to make this thing go no matter what. I don’t know how I’m going to get there. I don’t know what the path is, but I’m going to do it. And day by day, I’m going to figure it out.” And not just I. every person in the company has got to say that. We are together going to figure it out.

Struggles With RFID Standards

And so, yes, in 2003, Walmart made an announcement that they were going to tag all pallets and cases. This was great. It was fantastic. For a couple of small nits, we didn’t have any spectrum we could use. We didn’t have any wireless standard by which to communicate, and we didn’t have any products. Other than that, it was great.

On top of that, we didn’t have any money to buy spectrum. Spectrum is not a cheap thing. Building all the products and creating a worldwide standard for radio communications is not easy. People think Bluetooth and Wi-Fi. Well, we had to create the equivalent thing. We didn’t have it, and you cannot create a worldwide standard overnight.

We got to work, and we created a standard that finally got ratified in 2005 with an immense amount of work. It was the work of 100 PhD theses. It was just incredibly hard because it was doing your PhD thesis, and everybody’s fighting. Got the standard approved, but we had to build products to it. We still didn’t have spectrum. I personally spent a ton of time on that standard development effort. I was a project editor for it.

Then I went and met with the FCC. I joined TG34 in Europe which is the standards body associated with spectrum allocation. I presented in front of MEDI in Japan, and we did everything we could to get spectrum allocated for free. With the assistance of some large end users, we made it happen. In the meantime, the market all the hype went up. But with no spectrum, no standards, and no product, the thing came crashing back down again.

By 2006, it was a mess because we had just gotten some of the spectrum of things, but everybody was walking away saying, “This RFID stuff’s not going to work.”

It wasn’t until 2010 that we were far enough along from a product perspective and everything-else perspective that a couple of large retailers, Macy’s, Decathlon, Marks & Spencer, decided to adopt RFID for inventory tracking in their stores. And that was the beginning of the turnaround. We went through the typical Gartner Hype Cycle. Way up. More than $1 billion of VC money got poured into RFID when Walmart made that announcement way down, crashing down, and only one company of that whole time made it out the other side. It was luck. We were lucky enough that it was us. All the other companies failed or got acquired along the way.

Patrick: Chris, how many chips has Impinj made over the course of time? And where might the average person have encountered them, even though they didn’t know they were encountering them?

Chris: We’ve sold more than 100 billion chips to date.

Patrick: Let’s say that again. You didn’t say 100 million.

Chris: I did not. I said 100 billion. We’ve sold more than 100 billion chips. The industry has been growing at a 29% unit volume CAGR since the year 2010. At this point in time, we’re probably about 0.5% penetrated into the opportunity. The total opportunity is of the order of 10 trillion chips a year. I wish I had brought a vial. I have a vial that’s about the size of the end of my pinky that’s got half a million chips in it, and it’s tiny.

Where Impinj RFID Tags Are

They are effectively consumable silicon. We put the chips into our onto item. In retail stores, for example, let’s say for retail apparel and footwear tracking for inventory visibility in stores, the chips are generally inside the price label. If you hold up the price label to a light and look through it, you’ll see a little black dot. That’s our chip, and you’re mostly seeing the glue around the chip. And then a small antenna laminated into that label. When you get home, you cut off the label. You throw it out. You own the item, and then the retailer goes and buys a new item with a new chip. Every one of those chips identifies the item uniquely. Employees in stores go out with a handheld reader maybe twice a week and do a quick store inventory so the store knows what they have, knows what they need to order.

Going forward, we’re doing self-checkout systems, loss prevention systems, and other kind of systems to make the consumer buying experience much more seamless.

Patrick: On my phone, I have an app where my airline tells me where my bag is. When I do a road race, it tells me what my really bad 5K time is. That sounds like you must be involved in that somehow.

Chris: We’re involved in a lot of those things. If you fly Delta Airlines and use Track My Bags app, if you ever peel back one of the baggage tags, inside you’ll see an antenna with a little dot on it. Delta tracks your bag with what is now called RAIN RFID. RAIN for radio identification.

If you run a foot race, a 10K or something like that, there’s one of the chips with a little antenna in your bib, which you throw out at the end of the race. You don’t have to untie the tag and return it at the end of the race like in the old days. Our chips are on everything. If you think 100 billion, there’s roughly two billion people in the entire Western world. We’ve delivered roughly 50 chips for every person who’s listening to this call, and we’re just getting going. As I like to say, we’re the most pervasive technology that nobody’s ever heard of.

Tim: I love that. From a company building standpoint, it’s so fascinating because, again, you’re breaking new ground from a technology standpoint. You had to search around to find this set of use cases and product market fit, as we say. Even at that point, Delta and these retailers, there was a lot for them to bring together and write applications or track their inventory, et cetera. You’re sort of building the tech, evangelizing to end customers, building partnerships to integrate and take these things to market. That’s a hard set of things to pull off. Of course, back to people, you had some great people around the team, across both technology and the business side. How did you cultivated those end customer scenarios and the end customers while also working across all these partnerships?

Partnerships

Chris: One of the strange things in our industry, which you don’t see very often, is that our early adopter companies were some of the largest enterprises on the planet. Think Delta Airlines. Think Walmart. Think Macy’s. Think Decathlon, the largest sporting goods retailer. Think the Department of Defense. Think Department of Homeland Security. I mean, it’s these enormous-size companies or institutions. Hospital chains. We learned pretty early on that we needed to work with the large enterprises because they were the ones who could retool their operations and retool their supply chain to use what we were bringing to market.

The advantage there is our customers were huge. The disadvantage there is that they had huge operations, and it takes years for them to fully deploy.

Tim: I think an important lesson there for all startups, and even if they’re not targeting Walmart and Delta right out of the box, which you all did, is that you worked backward from the end customer, and then you had to develop the channel partners and integrators. You weren’t printing the hang tags with price tags on it, and neither is Walmart. Somebody else is doing that and somebody else goes and installs other things, et cetera, but you started with that end customer and said, “What’s the scenario?” You helped them cultivate, and then the whole solution and the partners necessary came together from that order.

Chris: We went to the end customer and said, “Tell us about the problems you’re having.” It’s about solving the enterprise problem. Tell us the problem you’re solving. We can solve this problem. Here’s what the solution will look like. The most important thing there, is establishing a trusted relationship with that enterprise customer. Truly a trusted relationship that you and they are in it together to solve their problem.

Financing Strategy

Patrick: Chris, I’d like to ask about how you thought about the financing strategy because you and your team have done a great job through the years of raising money when you needed it from value-added sources, and entrepreneurs and CEOs are always thinking, how do we view strategic investors versus financial? Early on in Impinj’s lifecycle, I think in the what we used to call the series B, I think maybe now it’d be called the series D.

You brought in three corporates as investors. TSMC, UPS, and Unilever. One of them, in particular, turned out to be an amazing long-term partner, and the other two were good partners also. But wondering if you had any thoughts on that, especially TSMC. Although they’ve been around for 40-plus years, recently they’re in the news because of all the supply chain issues and global issues regarding different countries and who makes what semiconductor. It’s very interesting because Impinj’s co-founder, Carver Mead, is the one that provided the intellectual and technical justification for the so-called fabless semiconductor industry. Morris Chang, who’s a very famous founder and CEO of TSMC, several times has publicly credited several conversations with Carver in the 1970s for the founding of TSMC. Yet here you are, a big customer of companies like TSMC.

Chris: Actually, two of those companies have had a very significant impact. Obviously, our relationship with TSMC that goes back more than 20 years, and we have worked closely with them, and they with us, to develop this technology and develop these chips. We chose TSMC early on because we did a bunch of technology evaluation. Back 20 years ago, TSMC wasn’t very big, but they had by far and away the best technology. We’ve had a partnership with TSMC ever since. Both their investment in us and that was a financial investment. Today, their investment in us in just a customer for them and the things they do to help us along as we develop new products.

The other one to look at is UPS. If you listen to UPS’s public statements by their CEO, they talk a lot about RFID, and they talk about tracking packages and the benefits it’s driving for their operations in terms of reducing miss loads, reducing miss shipments, and providing packages at the right place at the right time when they say they’re going to deliver it. I’d encourage you to go listen to some of those statements because it really is a testament to a company getting in early, understanding the benefits of the technology, seeing it as an opportunity for them, and then driving it forward. It’s an example of one of those Fortune 100 enterprises that takes time to adopt but has had the vision for a long time.

And I know, Patrick, you had a chance to meet with Morris Chang, going back to the TSMC.

Patrick: Chris, that was one of the thrills of my professional career. I was on the board of an optical networking company that happened to have a board meeting in Taipei because UMC, which was a TSMC competitor, was an investor. Because of you and Carver Mead, he sent an email, and the great Morris Chang and I had 20 minutes one-on-one at TSMC headquarters in Shinshu City. I was shaking the whole time because in my mind he was like Bill Gates and Jeff Bezos and Henry Ford all put together, but yet he was talking to the little old me, and it was because of you and Carver. He was such a nice gentleman. So smart. Had nothing but great things to say about Impinj even then. And this was 2002, I believe.

Chris: He is in the same mold as Carver and Tom Alberg from Madrona. I have no other way to characterize them other than wonderful people because they think about helping others along their journey.

Tim: Now one of the most valuable companies in the world and that a lot of folks hadn’t thought about until AI chips, NVIDIA, all those things. And there we mentioned AI. Now, we can move on. What a story.

I also just want to comment on Tom again, but he had such an influence on Impinj and, of course, on us here at Madrona. He did so many things that I think he did to help us all be successful, which is work with great people, empower them, take big bets, and then be patient. Probably more, but those all come through in how Impinj ultimately became successful and what we try to take into our investment philosophy today.

Tom Alberg’s Influence

Chris: Tom was a wonderful person, and we all miss Tom. He was wise. He was smart. He was trusting. He was helpful. He was patient and I wish he was still around. I really do. He was on our board from day one along with Patrick joining us on the board early on. Maybe at some point, you can tell your story about how he got to that board, but he was on our board from day one, and he stayed with us up until just a couple of years ago. I believe he was on two boards in the very early days. Amazon and us. I don’t remember when he stepped down. Maybe 2020. In that timeframe. His wisdom and the values that he brought to the company were immeasurable to our success.

Patrick: It was amazing because, when we first put the deal together for Impinj in 2000, we talked about this. Tom was on two boards then, Amazon and Impinj, and we were in awe of that. I think we were somewhat intimidated, but we really, really benefited from having someone of his caliber. He was such a great mentor to everyone that he touched. Specifically, how we put that deal together It combined a couple things.

Even though I wasn’t working at Madrona, I was sharing office space with Madrona, and Tom was happy to mentor anyone. Tom was one of my mentors. He gave me a lot of guidance for Impinj. I remember when we were negotiating the term sheet, Chris. Tom empowered me, and then my bosses at ARCH empowered me within a range. And then, Chris, you had a unique suggestion. Instead of coming over to your office and negotiating the term sheet, what did we wind up doing? And it’s a tool that I’ve heard you’ve used many times since.

Chris: We went on a walk. I do this a lot. We had obviously gone through the terms, and there were some sticking points. It’s often really hard to settle a negotiation around a table.

Oftentimes, and I do this with our enterprise customers as well, say, “You want to go on a walk?” Or, “Do you want to go on a run?” I’ve actually done deals on a run. And there’s something about going out and walking or running. Be careful if somebody’s a lot younger than you when you do the run one.

I remember it, Patrick. I said, “Patrick, what’s most important to you?” And he told me. And I said, “Well, here’s what’s most important to us.” How did we get to a resolution? We just walk and work through it. It was probably only 30 minutes, and we came back, and we were done. I’ve done that innumerable times with many customers out in the field.

The Fail-Fast Mantra

I’d like to go back to the investment topic for just a second. I hear this saying, especially coming out of Silicon Valley, that’s, “Fail fast.” If Impinj had been held to fail fast, we would’ve failed because there was no fast. As I said before, any transformative technology takes time. Everybody kind of takes mobile phones for granted today. It’s taken 40 years. I used the first mobile phone in 1985. It had a rotary dial. It was in a briefcase with a rotary dialed on a coil cord. The “fail fast” mantra works for disruptive approaches to existing problems where the foundation’s already built. Fail fast does not work when you’re inventing a new category.

The benefit of having Madrona and ARCH on our board was that they didn’t have the “fail fast” mantra. You guys had the “nurture the company to success” mantra, and Impinj was incredibly lucky. Incredibly lucky and thankful to have Madrona and ARCH as our first investors.

Tim: That’s kind, I mean, and it’s in the hardest parts about this business is riding the line between having patience versus putting good money after bad or falling in love with a bad idea. Tom was really good at this. I want to tie one other thing in here. I mean, Tom is clearly good at identifying talent and working with great people. You and Carver. Jeff Bezos early on. You’ve also done a great job. You came at it with a technical background. You were a professor at UW. You had some great business partners over the years. Bill Colleran. Evan Fein. You were not CEO. You’ve now been CEO again for a long time.

Any tips for newer founders? Your approach to hiring great people that aren’t technical? How did you hired heads of sales, heads of market, just in general? Do you have an approach? Is it something you had to learn over time? It’s always, I think, one of the hardest things is bringing on board great people in areas that maybe you’re not as comfortable with or don’t have as much experience with as a founder.

Chris: Tim, that’s probably the hardest thing in a company is to hire good people. You always make mistakes along the way. Then to be able to correct your mistakes relatively quickly because what you’ll find in a company is that bad apples, you will hire some, can cause immense damage. They don’t only cause damage financially or other things. They cause cultural damage.

The question is, how do you find the right people? I don’t know that there’s a way. You can write all this stuff down. You know all kinds of things. I haven’t found an institutionalized way to go at it. I meet with people. Spend time with them. I try and probe who they are. I ask them questions about some of the things that were most difficult for them, how they would approach problems, but they’re all basically ways of getting the person to open up and tell you who they are as a person. I don’t like to make a hiring decisions until I understand who a person is.

The Best Technical Question For Candidate Interviews

On the technical side, it’s easier for me. I’m going to share my cheating technical interview question. I haven’t figured out a way to do this on the non-technical side. But on the technical side, it’s really easy. Meet with somebody, and I say, “I’m going to give you 20 minutes to ask me any question you want. And then I’m just going to ask you one question.” And I’m going to tell you the question right now. You have 20 minutes to think about it.

The question is this: I want you to spend the rest of the interview and teach me something. It could be in any topic. Anything. I’ve had people go into soil biology. I’ve had people go into neuroscience. I’ve had people go into the details of spectrum analyzer design. Whatever it is, I want you to teach me. We did something in crypto, and we were deriving equations on the board. I want you to teach me something, and you can get a lot from a person by asking them to teach you something. You’re not asking them questions to probe what they don’t know. You’re asking them questions to probe what they do know. That’s the most important thing because, if they truly do know something, and they worked it all out, and they understand it, and I like it, you’ve learned something about the person.

Tim: So great.

Chris: Anyway, don’t steal my question all the time.

Tim: Why just technical? That’s a good question for anyone. If you understand something deeply, you should be able to teach it to me.

Chris: It’s harder to do on the sales side or something like that. I haven’t yet figured out an equivalent question if I’m hiring a sales lead or something, but it is a question I use fairly often.

Patrick: It’s such a great tool because, as you know, many tech companies, Bell Labs in the old days, Microsoft, they would ask these trick questions, and there’s no correlation between how you do. I was in an interview at Wall Street once, and they asked me, “If a chicken and a half leaves an egg and a half in a day and a half, how many eggs does one chicken lay in one day?” And that’s absolutely ridiculous. If you know the answer, you know the answer, right?

Chris: I would’ve said, “I don’t really like eggs. Next question.”

Tim: We got to talk about the IPO. Patrick had alluded to financing strategy over the years. You went public in 2016, as you alluded to. For those who don’t remember, 2016 was not exactly a go-go year for tech. There was a bit of a downturn in that timeframe for a variety of different reasons. Impinj had already been around 16 years.

Chris: We had outrun the funds that were initially funding us.

Tim: Tell us that story. And how did you manage to get public? And how was that then a springboard for what’s happened subsequently?

Chris: How did we manage to get public? Through a lot, again, of perseverance. We had tried previously and hadn’t had success just due to bad timing or events that happened. In a prior attempt, the market bottom-dropped out of the market just as we were about to go out.

A window opened in that 2016 timeframe. We decided to go. We put everything into it, and we focused on our story, this idea that we’re going to connect everything in our everyday world from point of manufacturing through the supply chain to point of sale, to consumer use, to end of life, beginning with the enterprise side. In so doing, we’re going to transform business operations. We’re going to transform people’s lives. That was the basis of the story. The industry has been growing at this pace. The opportunity’s here. All the pieces are in place.

We went out and told the story passionately. The IPO was hard. We did not have the most glamorous IPO. You can hear about all these glamorous IPOs. They’re flying here and there on private jets, and it’s easy and fancy. No, we didn’t get to do that. I think in the first week of the IPO, I ate at McDonald’s one night, Au Bon Pain one night, Subway one night, and one night on the train where all they had for food on the train was a bag of M&Ms, and I had a little half bottle of screw-top white wine. And that was dinner. But we did pull it off.

Tim: You ended up raising about $100 million in the valuation and the market cap after you went public was $400 million.

Chris: Yeah, it was. I don’t remember the numbers. It’s been too long ago.

Impinj’s IPO Journey

Tim: That was the order. I remember working on that together with you at the time. People talk about IPO windows being open or not open and that it’s this place that billions of dollars gets rained down. That was a financing, right?

Chris: It was a financing event, but it was a financing event through the public markets. And what the IPO really did for us is it opened the window to the financial markets so that, as we executed, we had access to more capital, and it basically allowed us to accelerate our trajectory and put more distance between us and our competitors. That was the benefit of the IPO.

Tim: It’s such a great story about IPOs being financings. I mean, in eight years since, it’s been almost 10x valuation. Market cap increases. Pretty hard to get 10x in any business, but post IPO in less than 10 years is incredible.

And another Tom story. I mean, he invested individually into the IPO, and that was a bit of a catalyst too and another kind of shrewd opportunity that he saw. 24 years in, still day one. You mentioned earlier 0.5% penetrated. Talk a little bit about the future of Impinj and the opportunity, the scenarios for consumers, for businesses that’s still unfolding around this cool technology that you’ve pioneered and created a category around.

Chris: When you use the term RFID, it’s about as broad as saying radio because there’s all kinds. NFC is RFID. Animal tagging. There’s all kinds of RFID. Key cards are RFID.

A couple years ago, we wanted to rebrand the industry in a name that was more consumer-facing because the future is really about consumers getting benefit from the connected items. We decided to rebrand the industry with RAIN, radio identification. That name has been a little slow to take hold, but I believe it will take hold.

There truly is a future coming where not just enterprises, but people get the benefit of connected items where you can locate the items in your house just due to readers in your house, and you know where things are. Where you can authenticate your medicine or authenticate items you buy either for authentication purposes or before you even purchase them.

A phone could easily be the reader in the future. And I don’t see any reason why it won’t be a reader in the future. People will be able to get information about their items using their phones, and you can almost think of it as kind of a AirTag, Apple AirTag-type model writ very broadly. That really is how I envision the future.

Every item that has value or interest to people, we can connect, and we’re going to do it. We’re going to extend the reach of the internet by a factor of 1,000 from powered electronic devices to things. That is the internet of things. We’re going to connect every thing. It’s going to be fun along the way. I’m just getting going. It’s good thing I’m still young. Not.

Patrick: To that end, Chris, 24 years and counting. Probably 25 because you were putting Impinj together this summer 25 years ago. You have the same physical, intellectual, and emotional energy that you had then. How do you do it? Any tips for CEOs out there?

Chris: Don’t get old.

Tim: Interesting advice from a physicist.

Work-Life Balance

Chris: Just keep going. I work hard, but I also play hard. Enjoy the time with your family. Enjoy the time when you’re not working. Enjoy the time when you are working. I guess that is the advice. If you really like what you’re doing, then it’s not work. I love my time at home. I’ve got a granddaughter now. She’s the joy of my life. I take time off work half a day every week, not counting the time, where I spend with her on the weekends, and I babysit for half a day. That’s my time blocked out of my calendar to go to be babysitting. And we play blocks. We read Dr. Seuss and all kinds of stuff. I get to do that, but I also love what I’m doing at work. And so, I guess that’s the story. Do what you love. Love what you do.

Tim: Thank you so much. You’re so generous with your time. You’ve built an amazing company and category.

Chris: No, no. We. We built an amazing company. You guys were on the team. We built a company.

Tim: That’s kind. I know Patrick and I have both learned a lot, and you’ve spent a lot of time mentoring and sharing advice, and this is another great example of that. Thank you so much.

Chris: Well, thank you.

Tim: Here’s to the next 25 years.

Chris: Well, thank you. Thank you.

Patrick: Thanks, Chris.

Chris: Thank you both very much. Thanks.

 

 

Listen on Spotify, Apple, Amazon, and Podcast Addict | Watch on YouTube.

In the latest episode of Founded & Funded, Madrona Managing Director Tim Porter hosts Pradeep Rathinam, a seasoned software executive with over three decades of leadership experience. Paddy was the Founder and CEO of Madrona portfolio company AnswerIQ, which Madrona invested in back in 2017. It was one of the early machine learning applied to SaaS companies that Madrona invested in. Paddy sold AnswerIQ in 2020 to Freshworks, where he started out as chief customer officer, helped take the company public, became chief revenue officer, and really drove a series of incredible accomplishments for Freshworks.

Today, Tim and Paddy dive into that world of SaaS go-to-market. Paddy shares his experiences on how to not just grow a company, as every company needs to do, but how to grow efficiently and how that includes reducing churn, expanding accounts, and landing new logos. This is something that all go-to-market leaders and startup founders have a lot of questions about how to unlock, so it is a must-listen for founders.

This transcript was automatically generated and edited for clarity.

Tim: So before we jump into the nitty gritty of efficient growth, tell us a little bit about the AnswerIQ story. You founded the company, built it up, and sold it in a relatively short period of time. Give our listeners some insights into what was AnswerIQ and why you decided to sell it.

Paddy: So perhaps the best thing I can do is start by introducing myself. So like you said, I’m old. I have three decades of experience.

Tim: I didn’t mean to highlight that. But I’m going on 30 years here as well. And it’s like, wow, there’s a lot of things that we’ve learned, isn’t there?

Paddy: The last decade is probably the most interesting for listeners here, I founded AnswerIQ, which was funded by Madrona. Thank you. It’s a classic B2B SaaS startup focused on using historical records to make predictions in customer service. We were using very early versions of GPT 2.5. And as I reached a pivotal point, which was — is this business going to grow to $100M or more? I reached the conclusion that being an AI layer sitting on top of customer service systems like Zendesk and Salesforce wasn’t necessarily going to get us to that $100M mark. So, in early 2020, prior to COVID, we sold our business to Freshworks.

Tim: Let me interject there quickly as we get into the Freshworks part of the story. I should mention that the AnswerIQ investment was led by my partner, Soma, and you had known Soma from Microsoft through the journey as well.

Paddy: That’s right.

Tim: In making that decision, was there strong alignment with the board? How did you work through that? Sometimes there can be a disagreement. Classically, the investor’s like, “We’re going to go for it,” or it could be the reverse. Was there a good alignment in that thought process that you alluded to?

Paddy: There was a very good alignment. Soma was an incredible board member and a dear friend. I think one of the things I learned in that experience was the simplicity of the questions that he asked, which was, “Hey, where do you see this business in five years? Do you see this business growing to a hundred million or a billion dollars? Do you see the path?” Once those became clear, it was alignment with the board to get everyone together to say, “Hey, let’s go out and find a transaction.” Freshworks was going for an IPO journey. I wanted to experience an IPO and I decided to jump on that bandwagon.

Tim: Freshworks, tell us that story.

Paddy: I joined Freshworks in 2020 as a chief customer officer. Those days, churn was the biggest challenge that the company was facing, and it was one of the key deterrents to its IPO and the net dollar retention. That was the first challenge I took on, built out the customer teams, and towards the end of three years, we reduced churn by over 40%. In post-IPO in 2022, our growth had slowed down significantly. We invested significantly in our field sales force, adding our investments by over 50%, and we saw a decline in new business in the field. I took on the challenge of the CRO to see how I could turn that tide. That was also an incredible year of sales transformation that we experienced.

In the end, it comes down to, like you said, why do founders stay or leave? For me, it was about what a mentor once told me — that being professionally rich its about the wealth of experiences you accumulate. It was about taking advantage of the opportunity to garner those experiences and learn from those.

Tim: When companies that I work with exit, I always encourage the founders stay on as long as you are learning a ton, and if you can have a big impact, this is a great opportunity. Yes, we’re in the startup business and it’s exciting like, let’s go do it again, let’s run it back. The notion of not just growing but growing efficiently has really been driven home. For those of us who’ve been working multiple decades, yes, businesses must be profitable and grow. Both are equally important.

There was a period leading up to really 2022 where it was sort of grow at all costs and you led through, it’s like, “No, we also need to be efficient.” When you’re a public company, and you’re reporting every quarter, it’s really glaring, and people are pushing on these things. But it’s incredibly important as a startup founder too. I mean the obvious, how long is my cash going to last? And so driving runway. I think efficiency through the full life cycle is critical in the market and everyone realizes that now, but it can be hard, especially as you’re also trying to significantly scale. Talk about your framework for thinking about efficient growth. What goes into that? What does it mean to you?

Paddy: Freshworks is a company that has over $600 million in revenue, creating SaaS products for IT service management, customer service, and CRM. With over 60,000 customers, we had three sales motions, which is PLG inbound, field outbound, and then partner-led. We had selling to three distinct buyers. We’re selling to a customer service leader, we’re selling to an IT leader as well as sales and marketing leaders. It’s a complex business in a lot of ways, right? When we started looking at this business, it’s not easy to break this down and say, “Hey, how do you really solve for growth?” Right after IPO, a year after that, like I said, we reached a crisis point where we created a 50% increase in our sales investment, and our new business declined in the field. All of these investments were essentially targeted.

Tim: That’s not efficient.

Paddy: Basically, all of them were targeted toward the field investments. We wanted to grow our ARR and ACV. I took on the challenge of the CRO, and one of the things I had to do was have a framework of how do you solve this problem. The first thing we did was look at deep analysis. I truly believe that growth for most companies lies within. If you’ve grown to a certain point that it’s 10, 50, or hundred million, there’s a reason why customers have bought you. There’s a reason that you need to go down and really analyze and be relentless in the analysis, whether it is by product, by geo, by SKU, by sales motion, really looking at both the economics, whether it’s CAC or LTV and those types of simple metrics or going into the mechanics of understanding and seeing what is going on with respect to win rates? What’s going on with respect to MQL-to-close and go-to-market efficiencies and engines?

Really looking holistically at the problem and saying, “How do we really break this problem down to see what’s going on in the business?” When growth stalls in a company, you typically will see the common view being the sales is broken. The go-to-market engine is not working or demand generation is not working. If you ask the sales folks, they’ll say, “Hey, the dog is not hunting.” The product isn’t really fit to what the market needs. It’s behind its competitive features when you compare AI with other competitors.

Tim: Wait, sales blaming product? Yes, that happens. Product blaming sales? Yes, to get in the blame game.

Paddy: It’s pretty common, but when growth stalls, it’s usually a structural problem that goes beyond go-to-market. Yes, there are go-to-market challenges but beyond that, when you look at product and mix what’s going on with product-market fit and pricing and packaging and competitive dynamics. It is a lot more complex than just looking at one dimension and saying, “Hey, we got to go do a go-to-market transformation and we’ll go find growth back again.”

Tim: You inherited a complex go-to-market, three different segments, three different buyers, and three different product lines; that’s a detailed matrix. What was kind of the range of deal sizes? If that’s something you can share, so the audience can orient because there’s sort of the big enterprise versus smaller deal size overlay on this too. Then, the first thing I’m taking away is to really know the data and follow the data. What did you do from there as you dug in?

Paddy: When we dug in, we realized two or three common patterns that were happening. The reason why our field new business had declined year-on-year was that the field was doing a lot of sub-$10K ACV deal. Imagine sitting here in the United States or in Europe or in Australia in some of these markets and building a sales force that is going out and selling sub-$10K deals. That was not cost-efficient and was primarily because of segmentation was broken. Our segmentation was such that more than 250 employees were belonged to what would be considered field. Looking at that data, one of the first things was to really break the mold and say, “Hey, we got to stop selling to a smaller segment of customers from the field,” number one. Number two, we got to sell a minimum ACV threshold, and we defined that as $30,000, and that became the core ICP.

More importantly, it was all products. Imagine a sales force running all products and selling them to three different buyers. It’s super complex. One of the things we did is simplify the motion saying, “Hey, we’re going to focus on one product that is going to be the winning cars.” We focused on IT. That was a product that was growing at 50% year-on-year. We made the sales force learn that one product and took all our other products and made them own to overlay and specialist sales force. What this is brought focus. Focus on IT, and on $30K plus ACV. We had competitors like ServiceNow, Ivanti, Cherwell, and we were winning in that marketplace. All we had to do was try and get the sales force to get focused on that.

Tim: The most important part of strategies is often deciding what not to do. That focus, I can see that being critical, simplifying things for your team. I often hear the conventional wisdom on what is the minimum ACV to be able to profitably sell direct with an outbound motion. Even at $30K, you have to be quite efficient, right? Sometimes I’ve heard $50K, it depends a bit, but 30K, while $10K seems very, very hard, even to achieve $30K probably took some real discipline and streamlining within the org.

Paddy: Yes, it is because when you are coming from $10K, $50K, $100K deals felt out of reach for a lot of our sales folks. Part of this was also transforming our sales force, the sales leadership, and the first-level leaders. First level leaders in sales organizations are the most critical path of really driving this. Once we got ourselves to a point of defining the ACV right, and we started transforming the sales force and because no GTM transformation happens without people. There along, we started getting more experienced salespeople, and we started selling a lot of $50K, a lot of $100K deals. $30K was the threshold, and, essentially, we created another aspect of it, which was our business was hybrid. A lot of B2B SaaS companies still operate with hybrid sellers, hunting and farming.

The reality is hunting is significantly harder than farming. A lot of farmers really got themselves into sellers, so we separated hunting from farming, and that brought a lot more incision and focus on the craft of hunting. We changed the incentive structures and so those were some of the things that we did just from a focus standpoint in basically saying, “Hey, focus on this ACV, narrow down.” The next thing we did was to add a lot more fuel to the fire. When you have three products, your marketing budget and your capital allocation tends to become evenly spread. We took from 40 cents to a dollar on our IT product to 70 cents to a dollar and saying, “Hey, that’s our core growth engine.”

Tim: Double down on what’s working.

Paddy: Double on what’s working. We saw that there was uphill challenges with our customer service product. Customer service as a landscape was going through a lot of change. Zendesk went private, growth rates pretty much stalled down, stalled for all our competitors. One of the things that I learned in my life is like, “Hey, don’t push uphill. Something’s got momentum. Go double down on it.” But trying to revive, the normal notion is we go try and fix this product and go back and sell and market. It takes 18 months, a product fix takes for 18 months, a product-market fit had changed. AI had changed the landscape of customer service, the expectation of productivity was high as well as the fact that the product itself had become more conversationally oriented. There’s a whole bunch of things that happened in the customer service space and I think that decision was a really good one to say, “Hey, let’s make that an add-on product that we sell through a specialist on overlay sales force and focus on IT.”

Tim: Can we double click just for a second on the change management aspect here? You looked at the data, you made these decisions, but then you alluded to the fact that it can be challenging to implement all that. It’s hard. I think I’ve seen whether you have eight people in your go-to-market team or you have 800. Certainly, more can be more challenging. Any lessons learned from the change management, both maybe your other peers around the exec table about hey, we’re not going to do these things and kind of letting go and then especially rolling out these changes to the field? You mentioned having to change out some folks. Was it a lot of rehiring? Was it training? Communication? What were some of the advice on doing that change management effectively? I know a lot of companies are going through this right now actually.

Paddy: Change management is hard. I think a lot of people think go-to-market transformation is about changing people and leaders. The reality is you want to bring them along and you want to give them an opportunity to really try and scale up. What we experienced was from a change management perspective, we did all of these changes in 45 days. So we weren’t doing a great job. What we did is give people a break for the first quarter and make sure they picked between wanting to be a hunter or be a farmer. These kinds of changes were very, very important because people suddenly felt like a goldmine of existing customers that they sold to went away.

And so change management has to be gradual. It has to be thought through. There is no good change management simple principle that you can say — The only thing I can say is to over-communicate and make sure that you bring people along and set expectations that it’s going to take time for these changes to land. It took us 1, 2, 3, probably on the fourth quarter, at the end of 2023, we had the largest quarter in six quarters. North America did its biggest business. It takes time for all of these things to land if you will.

Tim: It can be hard to get people selling $10K deals to selling $30, $50, $100, but it wasn’t just a wholesale. We have to get rid of our existing sales force and add new ones, bring people along, retrain, communicate. Sure, getting the comp piece of it all aligned, incentives aligned with the direction as well. That’s good to hear. Patience and intentional communication sounds like the key. That’s often the right answer, is it? Even in our family lives.

Paddy: It’s harder to said than done. People always will say, “Hey, this did not work well. Mindset is not right.” But overall, I’d say as we went past the six-month mark, there were no questions asked. Everybody was like, “Hey, this is the right strategy. Let’s just go and double down and win here.”

Tim: That’s the other thing. Once you start winning, that’s what aligns everyone. Everyone wants to win. You alluded to something in that description around hunting and farming. You also said it’s much easier to kind of grow from your existing customers than to find new ones. That hunting is much more expensive than farming. That being said, new business is the lifeblood. It’s oxygen. You have to also add new logos to then do the expansion pieces. We can come back to the expansion side of it, which is super critical. I think, especially in a down market, we’re adding new logos is that much harder, but you were able to do both. Maybe talk about the new business piece. It’s the hardest and most expensive, yet you found ways to do that efficiently. How did you do that, Paddy?

Paddy: New business is probably the hardest part in any enterprise field motion. It’s not repeatable. It’s long. It’s expensive, it’s time-consuming. In the end, the only thing that people say there is a sales process that’s repeatable, but the magic of new business is hard. One of the things I talked about is the focus. We focused on North America. We focused on winning in our ICP, which was on $30K plus ARR, competing with ServiceNow, Cherwell, Ivanti, and some of the competitors. Once we put all of these dimensions, then we had to make sure both our recruiting changed to make sure we got the right caliber of people. We changed our enablement, which used to take six months, down to one month of enablement. There’s a set of things that you need to do to get your new business motion right. We changed the incentive structure for multi-year contracts and larger deals.

Tim: How did you pay on that? Did you pay for the full multiyear upfront or what was the from-to?

Paddy: There were kickers. There were kickers for multiyear, and essentially, one of the things that we did was to make sure we made a target that was quarterly coders. It was really about you can make a lot of money, but the idea around the fact that you only are surviving on hunting was a new notion in Freshworks. We really made all of these changes. Then the other thing was, as soon as we put 70 cents to a dollar on our marketing on IT, we started seeing some repeatability. Now storytelling is very important. The alignment between sales and marketing is critical. You get that right, and then you start seeing momentum.

Tim: Did you own marketing as well?

Paddy: No, I did not own marketing.

Tim: Okay. So it was another tricky alignment piece is to work with your peers who are running marketing to drive this alignment.

Paddy: This is an area where I would say there shouldn’t be a ray of sunshine between sales and marketing because goal alignment is important. You want to be able to make sure that everybody is talking the same language. Businesses are measured on quarterly revenue. Salespeople are running on quarterly revenue, but often you’ll find marketing teams being misaligned because they are on an annual incentive plan, annual plan, corporate plan. The reality is MQL (Marketing Qualified Lead) is no good if it is not converting into business. And so getting marketing leader and alignment in my view, ought to be much more closer to the sales incentive alignment on a quarterly basis.

Tim: That is a common one where the MQL is elusive. You, of course, need top of the funnel to get at bottom of funnel, but you can have lots of MQL that aren’t actually qualified. Did you pick sales opportunity? How did you align? What’s the marketing to sales funnel metric that mattered at Freshworks?

Paddy: MQL-to-SAL (Sale Accepted Lead) and then SAL-to-close, and the reality was MQL-to-close was also a number to really understand. In SaaS business, these are very, very hard metrics to really point to. I do think that once you align the leadership teams on the same goals, I think you will start seeing a lot more teamwork and collaboration on these areas.

Tim: With the lead-gen motion? I’m sure marketing was doing inbound programs where they’re kind of out doing marketing things, generating leads that get handed off to sales. What about the outbound motion? Was there a BDR function, and were those people under marketing, or were they under you? That’s another place where I feel like there are six of one and half dozen of the other can depend on the leaders that are in place, but that’s a place you can often get the alignment wrong.

Paddy: And I think we got it wrong. I do believe that the BDR team belonged to my organization and the CRO organization. The reality is if you align your BDR team and marketing teams much closer and if they’re on that team, everything from messaging, because when a customer picks up the phone or is a response to an email, the language, the words, the nuances, that’s where you learn your messaging, outside of talking to your existing customers and talking, why did they buy you and what was the trigger points? The reality is BDR (Business Development) teams actually see tremendous synergy with marketing and putting them together, making sure that everything from MQL-to-SAL is all well packaged together, is probably one of the things I would say is a better alignment from a sales and marketing perspective.

Tim: What was the dominant lead gen source? Was it the BDR function or was it inbound or was it pretty evenly split?

Paddy: It was the BDR function.

Tim: BDR function. So getting that tuned was critical.

Paddy: Getting that tuned was very critical. BDR function is hard, especially post-COVID. It’s very hard for people to pick up phones, emails are hard to read. And so really using new innovative methods, trying to understand how to get better on LinkedIn. Those were the types of things that one would do. I would still think that getting these two functions tightly aligned would really change demand generation. Demand generation is hard. It’s a crowded marketplace. It’s hard to get your message out there. I feel for marketing leaders because simple storytelling is hard today. A big part of what’s missing in today’s industry is the ability to tell a story that a fourth-grader would understand. That’s the compelling message and that stays memorable, right? With SaaS, that’s very hard in a crowded category. Of course, if you are Copilot for GitHub, you got it all easy.

Tim: Let’s shift gears to retention. So this is the other side of we were talking about new logo, but customer retention is you have to do it. It’s more profitable, it should be easier. On the other hand, coming out of this period of time where every single dollar in the budget is under scrutiny from the CFO, can be harder. I know with some of our companies in 2023, I sort of said, “The theme this year, first and foremost, is retention.” We have seen even with that focus, net retention rates have dropped across SaaS. If you look at the overall numbers, certain things like seats weren’t growing naturally, consumption wasn’t growing net as naturally. How did you think about customer retention? Sort of interesting since your AnswerIQ is sort of in this support retention kind of area, but critical for you at Freshworks, how did you approach that side of the coin?

Paddy: Freshworks had a unique challenge. One, because of selling to SMB, churn tends to be natural on one end. On the other hand, with 60,000 customers with the PLG motion, you tend to see higher churn rates in some of those types of businesses. What we did was to simply start, and I have a very simple equation, which is retention = adoption + engagement + advocacy. These are the three core pillars, but it all starts with adoption.

Tim: I like that retention = adoption + engagement + advocacy. Let’s decompose that a little bit on those different pieces.

Paddy: That’s how I set up the entire team’s charter. The customer organization was thinking about this, but the most important thing for SaaS businesses is adoption. It all starts with product. Understanding product telemetry, picking up the right telemetry that you know as a business that will retain your customer or the customer will stay with you for long is critical. Most businesses, if you ask me, they’ll collect tons of metrics, tens and tons of metrics, but can’t make sense of what does retention really mean. We used a framework saying, hey, let’s look at cohorts of customers by revenue sizes, by industry, by usage scenarios across all of these. And basically said, how do we look at the top five to seven features that essentially a customer that has been staying with us for long is using? That’s what we call a pack called essentials.

We created a package called advanced and one for ultimate. It was deeper usage of features. Feature usage and adoption, not as a feature, but in the usage scenario is critical. Being able to see from a telemetry and understand was important. We go CSMs and our customer success and account management organization saying you got to move customers from essentials to advance to ultimate. The ultimate, we knew all the integrations. We knew when people were bringing data into our system, they were less likely to leave. There’s a framework you can think through, but it all starts with telemetry and being strategic about telemetry is very, very critical in today, in the way you think about product adoption.

Tim: That’s fascinating. I think most of the companies I work with realize, hey, we need to have this telemetry, otherwise, we’re flying blind. The customer’s actually using it and the product, of course, has to be compelling that draws people in, et cetera. The packaging, the SKUs as a way to not sort of drive more monetization but actually to drive more usage. That’s a really interesting insight.

Paddy: It was not only usage, it was an upsell strategy too. It was a little bit of both because we knew if someone was in advanced or ultimate, they would actually go to higher, higher-level plans of our product. The second part of it was onboarding.

Tim: If you don’t set people on the right course, it’s hard to get them saved over time.

Paddy: Absolutely. And the first hour in PLG SaaS business, the first day in SaaS business is important in a trial period, but the onboarding experience that you offer and what you learn from that is the Achilles’ heel in SaaS business, because some businesses take 30 days for time to value, some take nine months for time to value. The reality is you’ve got to understand what is it that the customer is asking for and how do you understand what are you setting up for the customer and taking that, feeding that back into the product team.That’s where a self-service onboarding can become significantly better. We created a package for digital adoption where we took onboarding for free for six hours for 15,000 plus customers. It was massive in our churn reduction initiative.

Tim: Before that digital pack, was this not offered or did you charge for it?

Paddy: It wasn’t offered. It wasn’t thought through. A big part of this was to create a simple package. Once you had essentials advanced, go take essentials, get it done with customers, and we knew the customer had a higher opportunity to stay with us.

Tim: Do you do any free trial or POCs before people decide to adopt? And at what point did you layer on this digital pack for the kind of free onboarding training?

Paddy:All our products have a free trial, and then for a field and enterprise, you take them through a POC. The reality is go live is a misnomer. Usually, it’s a .one, it’s an MVP, but there’s a lot of work to make that product work after that, and so understanding those pieces were critical from the churn perspective. Onboarding was a critical path in making sure that you can make it very easy as well as you can do it at scale. That was one of the things that helped us reduce churn.

Tim: Onboarding needs to start at the free trial or POC, or you probably don’t convert to paid, but also once they’re converted to paid that go live, that’s a misnomer too because it has to continue to make them successful.

Paddy: That’s right. Yeah, because to see value takes a lot more than just the go light that they have. There’s more work to be done. The third area was around customer service and support, right? Think about it. It’s a goldmine of signals, ongoing touch points, with the customer. This is a place where you see customers reach out to you because the product is not working in a certain way or there are certain things that can’t work and even developers tend to think about is a simple feature, why can’t the customer use it? We learned a lot from the contact rate. Reducing contact rate, understanding contact rate, and getting the right codification on that is critical from a churn perspective.

You get this right. We had an amazing partnership with the product team where we said we want to bring down contact rate by 5% every quarter for the top contact codes, but contact coding also requires a lot of strategic thinking in terms of how you do the coding, so that way, you can really take that feedback back to the product team. All of these three areas are very core to what I call product related and product telemetry related in terms of an adoption perspective.

Tim: Your first part of your attention equation adoption, just to summarize, first, the product has to be wired so you have the right telemetry in place and you use it. Second, you have to get the onboarding right to really get them to adopt. Then there’s this ongoing contact rate, which is probably a segue to engagement, which that’s the next part of the equation to how do you solve retention.

Paddy: Right. So engagement is an overused term in the industry. People do QBRs with the person they meet on a weekly basis, and they will talk about how’s the health of the system and what have you. The reality is engagement really works when you have a strategic relationship with an executive on the other side. One of the things that we did was enforce this thing called the executive business review. In that, we wanted to ask the business leader on the other side, your simple questions like saying, “Hey, here are the best practices. Here’s what other customers are seeing from the product and how they’re benefiting from this.” Then ask the straight question, if you were to ask you today, would you renew or not? There’s no point in asking a lower-level stakeholder. You want to take this to the right level.

Executive business reviews are hard. Generally, you will not find the ability for a lot of sales leaders, account leaders, success leaders, being able to go and ask the questions saying, hey, I want to talk to a C-level person on the other side, because conversations are simple. The conversations are, hey, are you doing something to improve their customer experience? Are you doing something to reduce their cost? Are you doing something to improve their avenues? If it’s none of these three, and then what is the practice that’s used by their competitors that you can take to them? That is where the executive business reviews really works.

We had the top 100 customers adopted by execs. Every C-suite person inside the company had to own 10 customers. For example, we had a voice of customer once every month. We would get three customers to come and speak into the management team and just keep their verbatim feedback without being any coaching, without giving any coaching. Those were signals that we would learn from the engagement perspective to understand, hey, in the top tier, mid-tier, the bottom tier of customers, how are customers perceiving their relationship with the company?

Tim: That executive buy-in, it sounds obvious, but it’s so critical. I’ve seen so many times where, hey, the customer’s using it, they love it, the daily champions, but then you might get the legs cut out from under you a time of renewal because execs didn’t see the value, got rid of budget, or maybe were getting sold to by a competitor that comes in top down. When you talk to teams, it’s like, “Are the executives buy in?” “Oh, yeah, yeah, yeah, they are, they are,” right? Because if you might be just listening to your champion and they might not have it. So this point about enforcing that discipline and creating some mechanisms to ensure that those EBRs happen, et cetera, I think that’s really good advice.

Paddy: That’s right. Companies tend not to spend as much focus on this, but I do think that being very disciplined around the executive focus is a sure-shot way to make sure that you have customers who are happy.

Tim: We’ve been talking about change management and org alignment. There’s also interesting on your side. You referenced different execs across Freshworks that had customers, but there’s also always this question of was this an account management function? Was it a customer success function? Did you have both? How did those orgs dovetail to accomplish this set of things?

Paddy: We did an interesting exercise and one of the things was, how do we put the customer at the center and have these teams work with each other? If you look at what was what happens, it’s a blame game between, hey, this is not an expansion opportunity. This is a retention opportunity option thing. CSM works. CSM tells it’s a renewal opportunity and account managers take it. What we did is we built a pod. We made the account management and CSM function under one same set of customers. Account manager focused 70% on expansion, 30% on churn. Customer success leader manager focused on 70% on churn and 30% on expansion, and they worked like magic. Now, you put the customer in the center, EBRs and QBRs were happening, adoption packages were being sold in. There are things that we did that essentially structurally brought, which makes sense because hey, it’s the customer is at the center, why do we have two teams in two different organizations to really work with the customer?

Tim: Okay, last piece of the retention equation, advocacy, I would guess that’s the one. It’s like, okay, what does that mean exactly? I kind of get the, they got to use it, and we got to engage over time, but what is the advocacy piece and how does that bring it all together?

Paddy: Advocacy is the network effect, and I think if you see customers like to talk to other customers because being in a community is also a sense of, well-being, being part of something, learning from others, learning from others experiences. Advocacy became one of the goals where we say, if we can get a company to publicly say with us, say that they’re using us and this is the benefit that deriving, you would get CSM incentives and points on that. Driving that became a critical factor. One of the best things we found with advocacy was that when our advocacy worked well, we bought a lot of net new customers. The new business customers, when they came into some of these forums and they felt like, hey, they’re seeing other customers talk, that was probably one of the magical moments for them to say, hey, I think these guys are transparent. They’re talking about the product, the company’s listening, and the magic happens for new business there.

Tim: Retention = adoption + engagement + advocacy.

That’s good to remember. By the way, Paddy has published some blogs in some of these learnings, so we can point to those later. You can go and read more and learn more about some of the details here. Let’s move to one other key area here, and you alluded to it. There’s new logo, there’s keep the logos that you have, but then how do you expand within them? When you were talking about account management and CSM alignment, you teased the expansion question different ways that you can expand in accounts. There’s upsell, there’s cross-selling, other products, SKUs, et cetera. What was your approach to driving expansion and keeping customers happy at the same time at Freshworks?

Paddy: First principles, expansion can’t happen unless you have deep product adoption, you have advocacy, and you have a happy customer. To go back at renewal and say, “Hey, I want to expand my revenue or plan three months before,” is not necessarily the best path for expansion. Expansion, in my view, is one of the areas where product managers, product leaders, have to be very, very strategic about thinking about what is the roadmap for growth from an existing customer. It’s not so much of an account management function, but really the set of SKUs, the offerings, how do you package AI beyond Copilot?

Those are the types of things that product leaders need to think through because that is where the rubber meets the road. When I look at product management today, pretty much most SKUs are designed around T-shirt sizing: small, medium, large. You look at a competitor, you say, “Hey, let’s don’t match that.” The reality is you can learn from telemetry, you can think about usage. How do you increase usage and consumption in different ways in the way you design your SKUs, right? A big part of what I think about expansion is making sure that you have a slew of offerings that account managers have in their armory when they go to customers, and then be able to really talk with the best practices that other customers are using so that they can get them.

Tim: Were there any mechanisms internally to take all those learnings from your go-to-market org and feed it back into product management? Was it as simple as, hey, we communicated a lot, or was there anything that you did there to make sure that those learnings transferred in the right decisions that you referred to ultimately got made?

Paddy: A lot of it would come through the quarterly product reviews. In our business, we have a quarterly product review, and so in the core quarterly product review, you have sales, account management, CSM, everybody bringing in the feedback, customer success, customer support, onboarding teams to the product teams. It was, while it was not so structured, it was a forum every quarter to bring some of this back to the product teams. The second aspect is when you think about the amount of effort that businesses spend in the amount of money, in resources, in marketing, in sales towards new business, expansion marketing teams are relatively underfunded in most businesses. It is a lost opportunity.

It is a lost opportunity in the sense that, hey, not only can you drive more advocacy, you can drive more adoption, but systematically thinking about expansion marketing is very, very critical. I do feel that it is underfunded in most organizations, because everybody is basically smitten by the new business growth that one wants to get. One other aspect I will add is how do you make this more product led? The reason why I was putting it back product leaders is because making expansion more discoverable, which is how do you get more features, aspects of your products, your cross-sell upsell more discoverable in the experience of the product is critical. I think there is still a lot of room for growth in SaaS businesses to do that better.

Tim: You brought up earlier the pricing packaging aspect of this. Is there anything you did around structuring contracts that was also helpful in encouraging expansion or any tips on that side of things?

Paddy: From a contracting perspective, it’s pretty obvious. One of the things that you’ll find is most SaaS businesses discount heavily on year one and sometimes end up discounting for multiyears because of the desperation of winning that deal. It’s very important upfront to start thinking about whether it’s expansion rates that you apply, limits you apply for usage in how you package your structure of the deal in such a way that you continuously get on renewal rates, ARPA improvements, as well as expansion of the new expansion dollars that you can see. And I think that is definitely one of the areas I would say that SaaS businesses ought to do better. The big guys like Salesforce and Oracle, they steamroll you and do that. But generally, when you see startups and midsize companies, they struggle to find that voice and that muscle to be able to do so, and I would understand.

Tim: Panic a little bit right in discounts. So the advice is maybe like yes, as a startup, you have to realize you don’t have the pricing power of Salesforce, but maybe don’t get desperate too quickly.

Paddy: Yes, especially at the point of sale.

Tim: It’s harder than you think to make it up in year two and year three.

Paddy: You have the customer. The customers agreed to buy. I mean, I think at this point, you don’t give in on some of these areas.

Tim: Wow, what a fascinating journey and amazing success at Freshworks. If you tie this all the way back to startup founders and thinking back to your time leading founding AnswerIQ and having been a CRO here for these last several years, what do you think about org building there at earlier stage companies? This is always a question, when do we bring on a CRO? Any advice about that or general org building now for the early-stage companies that were maybe in that kind of first three-year journey that you took AnswerIQ through?

Paddy: Most startups go with head of sales to start with, and then they bring on a CRO at a later stage. CRO to me is a strange title, right? The title by itself has so little leverage. The customer’s only thinking about getting discounts from you. There’s no value conversation you can have with the CRO title because you have the name revenue written on it. Besides that point, the three things in a startup, you have to build are, you got to sell, and you got to tell. In the initial stages of a startup, a CRO is the seller and the teller because you’re learning from your customers and you’re building your story as you go along. It’s a critical function that you bring on early that is lockstep it the way you’re building your product and you drive growth for your business.

Tim: Paddy, this has been absolutely terrific. I know that the absolute most common set of questions we get from founders are all of these things we’ve been talking about around go-to-market, the decisions, the organization, the levers, what good looks like. This is incredibly useful to our audience. Again, Paddy has written some blogs that go into more depth. We’ll have links to those in the episode notes, but I can’t thank you enough for sharing your time and your insights with us here today in Founded & Funded.

Paddy: Thanks, Tim. Thanks for having me.